ANTENNA SPHERICAL COORDINATE SYSTEMS AND THEIR APPLICATION IN COMBINING RESULTS FROM DIFFERENT ANTENNA ORIENTATIONS

Size: px
Start display at page:

Download "ANTENNA SPHERICAL COORDINATE SYSTEMS AND THEIR APPLICATION IN COMBINING RESULTS FROM DIFFERENT ANTENNA ORIENTATIONS"

Transcription

1 NTNN SPHRICL COORDINT SSTMS ND THIR PPLICTION IN COMBINING RSULTS FROM DIFFRNT NTNN ORINTTIONS llen C. Newell, Greg Hindman Nearfield Systems Incorporated rd St. Bldg. 524 Carson, C 9745 US BSTRCT Te results of teoretical calculations or measurements on antennas are generally given in terms of te vector components of te radiated electric field as a function of direction or position. Bot te vector components and te direction parameters must be defined wit respect to a sperical coordinate system fixed to te antenna. long te principal planes tere is no ambiguity about te terms suc as vertical or orizontal component, but off te principal planes te definition of directions and vector components depends on ow te sperical coordinate system is defined. Tis paper will define four different sperical coordinates tat are commonly used in measurements and calculations, suggest a terminology tat is useful to distinguis between tem, and define te matematical transformations between tem. One important application of tese concepts arises wen comparing or combining measurement results from two antenna orientations. In tis case, te axis of rotation dictates te preferred coordinate system and vector components. Measured results will be sown to illustrate te proper coice of coordinates for eac situation. accomplised, te - - and -axes remain fixed to te antenna and do not cange for any of te sperical coordinate systems tat will be discussed. q 1. INTRODUCTION n antenna coordinate system is implicit in almost every antenna measurement. Terms suc as pattern, main and crosscomponent, beam pointing and peak gain, imply te definition of directions and/or vector field components wic require a coordinate system. Reference is often made to te crosscomponent of an antenna as if tere is a unique definition of suc a quantity wen in fact te cross-component as well as te main component will depend on wic coordinate system is used and ow it is oriented wit respect to te antenna. mbiguity and confusion can be avoided by using precise definitions and a terminology tat distinguises te different coordinates. Ludwig 1 proposed suc a terminology, and it is widely used. It does not clearly define all te coordinate systems commonly used owever, and te following discussion will propose additions to te Ludwig terminology. 2.THT PHI SPHRICL COORDINTS We begin by defining te -- axes of te antenna coordinate system suc tat te main beam is approximately along te -axis. Te - or -axes are defined approximately coincident wit te major polarization axis as sown in Figure 1. Te precise definition of te axes location and orientation must be accomplised by using fiducial marks, alignment mirrors or optical telescopes. Once tis definition is Figure 1 q-f Sperical Coordinates Te sperical coordinates sown in Figure 1 are te usual - coordinates wit te -axis as te polar axis. Te spere surrounding te antenna sould be muc larger tan te antenna since it represents te spere on wic te far-field vector components are measured or represented. For convenience it is sown just enclosing te antenna. Wit tis coordinate system, directions are specified by te angles (,) and vector components by te unit vectors q and f. Te rotator system used for tis coordinate system is te roll over azimut positioner sown in Figure 1. In a far field measurement, a vertically polarized source antenna illuminates te UT wit a field tat is polarized in te f-direction and te received signal will ten correspond to te -component pattern. orizontally polarized source will produce te -component pattern. It is important to note tat wen te antenna is rotated, te spere defining te sperical coordinates and components stays fixed to te UT and also rotates. Te spere is used to define te pattern radiated by te UT as a function of coordinates fixed to te antenna. Tis spere is not used to specify te directions te main beam points relative to axes fixed in space as te angles are canged.

2 v (, ) = (, )cos (, )sin (, ) = (, )sin + (, )cos v Corresponding transformations will be sown for all te coordinate systems. 4.LUDWIG-2, IMUTH-LVTION COMPONNTS (1) Tere are actually two coordinate systems tat come under te Ludwig-2 definition. Tey correspond to different types of far-field rotators and te corresponding orientations of te polar axis of te sperical coordinates. Te - components are used wit te zimut over levation rotator sown in Figure 3 were te polar axis is coincident wit te -axis. Figure 2 Ludwig-3 or -v vector components. If te UT is linearly polarized, te vectors q and f sown in Figure 1 are not te most appropriate for specifying te field vectors since in te region of te main beam te vectors cange direction relative to te antenna as a function of. Te orientation of te -axis relative to te antenna could be canged to define new sperical coordinates, but tere are some situations were te current definition is preferable, and it also makes it muc easier to transform between te oter sperical coordinates if we retain tis definition for te q f sperical coordinates. x 3. LUDWIG-3 OR H-V VCTOR COMPONNTS modification of te - components overcomes te polarization problem noted above, and is widely used in anecoic camber measurements. Te q and f unit vectors are rotated about te radial direction by te angle to obtain te vector components referred to as Ludwig-3 components. We ave used te notation and v to refer to tese components since tey define vectors tat are respectively approximately orizontal (parallel to te x-axis) and vertical (parallel to te y-axis) over most of te emispere. Te resulting coordinates and vectors for tis coordinate system are sown in Figure 2. In a far-field measurement using te Ludwig-3 components, te source antenna is rotated about its axis by te angle in syncronization wit te UT -rotation. If te magnitude and pase of two components in one system are known, te components in te oter one are found from te following transformations. Figure 3 z-l Coordinate system and azimut over elevation rotator. Wit tis rotator, te origin of te UT coordinate system is not centered on te antenna. It is at te intersection of te two axes of rotation, wic is inside te mecanical structure. Tis will not effect te far-field amplitude pattern, but will cange te pase pattern. Te rotation of te spere wit te UT for tis coordinate system is apparent in Figure 4 were te UT as been rotated in bot zimut and levation. Te point on te spere wit coordinates (,) is now along te line from te origin to te source antenna, and te and components at tis location will be measured by orizontally and vertically polarized source antennas respectively. Te transformations between - components and - components is given by,

3 cos (, ) cos sin = (, ) cos cos (, ) (2) were cos sin cos (, ) = (, ) + cos cos (, ) 2 cos = 1 (sin sin ). (3) Te angles in te different coordinate systems are related by, sin cos = cos sin = sin α, sin sin = sin = sin ε, (6) cos = cos cos = cos ε. e a Figure 5 a-e coordinate system wit associated elevation over azimut rotator. Figure 4 Rotated azimut over elevation rotator. 5. LUDWIG-2 LPH-PSILON COMPONNTS Te oter Ludwig-2 components are associated wit an elevation over azimut rotator were te polar axis is coincident wit te -axis sown in Figure 5. Te transformations for tese components are, cos cos sin Ε ( α, ε) = Ε (, ) Ε α sin cos cos Ε ( α, ε) = Ε (, ) + Ε ε cos sin Sin Εα ( α, ε) = Ε (, ) Ε sin Sin cos Ε ε ( α, ε) = Ε (, ) + Ε (, ) (, ) (, ) (, ) (4) (5) long te xz principal plane, Ε (, ) = Ε ( α, ) = Ε (, or) = ± Ε (, or) Ε (, ) = Ε ( α, ) = Ε (, or) = ± Ε (, or) α ε v nd along te yz-principal plane, Ε (, ) = Ε α (, ε) = Ε (, ± ) = mε (, ± ) 2 2 (8) Ε (, ) = Ε ε (, ε ) = Ε v (, ± ) = ± Ε (, ± ) 2 2 Terefore along te principal planes, tere is little or no difference between te components, but as we move off te principal planes, te differences increase. Tis means for example tat if a far-field measurement using an levation over zimut rotator is compared to te results of a near-field measurement, te comparison will depend on wic components are used in te near-field program. ll te components will sow good correlation along te principal planes, owever in directions off te principal planes, only te α-ε components will sow good agreement wit te L/ far-field measurements. If measured results from near-field, (7)

4 far-field or anecoic measurements are compared to teoretical predictions, te vector components must be te same for measurement and teory or te results will not agree. Suc disagreement can mistakenly be interpreted as indication of problems wit measurements or antenna construction wen te actual cause is an inconsistent coice of coordinate systems. 6. COMBINING RSULTS FROM DIFFRNT NTNN ORINTTIONS noter measurement application tat requires te proper coice of bot te vector components and te coordinate system used to define directions as recently been developed at Nearfield Systems Inc. Tis application uses two or more planar near-field measurements on te same antenna were te antenna is rotated about one axis between eac measurement. Te results of tese measurements can be used to extend te angular coverage of te planar near-field measurements or to estimate te magnitude of specific errors in a measurement. Bot of tese applications will be illustrated. Relative mplitude in db -4 Deg Beam Figure 7 Illustrating te increase in angular coverage by combining steered beams. +2 Deg Beam -2 Deg Beam zimut ngle in Degrees system defines a direction or location in space and te vector components define two ortogonal components of te electric field. In a sense te "natural" coordinate system is te one tat corresponds to te vector components since te field vectors are along te lines of te corresponding coordinates. In te specific case of a rotated coordinate system, tere is a compelling reason to use a specific coordinate system and a specific set of vector components as te "initial" or "natural" set. For rotation about te z-axis,, coordinates and vector components are te natural coice. For rotation about te x- axis, α, ε coordinates and vector components are te natural coice. For rotation about te y-axis,, coordinates and vector components are te natural coice. If tese natural coordinates and components are cosen tere will not be any cange in te sape of te pattern due to rotation, only an offset. Once te offset as been taken care of, we can always convert to any oter components or coordinates. Figure 6 Slot rray test antenna in initial unrotated orientation. Te angular coverage of planar near-field measurements is limited by te size of te scan plane, and te region of validity is defined by te angle between te edge of te UT and te edge of te scan plane. In some applications, results are required over a larger angular region tan is possible wit te available scanner. Te angular coverage can be increased by rotating te antenna and repeating te measurement. Te results of te two measurements are ten combined. Successful combination depends on using bot te coordinate system and vector components tat are appropriate for te antenna rotation. In general for a single antenna orientation, any coordinate system suc as (x, y, z); (k x, k y, k z ), (, ); (α, ε); or (, ); can be used wit any vector components since te coordinate Figure 6 sows te antenna tat was used for te following tests in its initial orientation wit te main beam normal to te scan plane. It is an -Band slotted array approximately 14 inces in diameter. Wit a measurement lengt of 6 inces in x and y, and a z-distance of 8 inces, te resulting far-field pattern is valid over ±7 degrees in bot azimut and elevation. To increase te angular coverage in te azimut direction, te antenna was rotated +2 degrees about te y- axis using a rotator tat was aligned wit its axis of rotation parallel to te y-axis of te scanner. Tis corresponds to te zimut angle of te coordinate system sown in Figure 3. Near-field measurements were repeated, for tis antenna orientation and for a similar rotation of 2 degrees in zimut. Figure 7 sows te results of tese tree measurements along te orizontal principal plane. Te +2 degree and 2 degree patterns ave been sifted to put te peak on-axis for tis display. Te az imutal coverage as now been increased to ± 9 degrees and it is apparent tat te patterns sow very good agreement witin teir common regions of validity.

5 Relative mplitude in db Degrees + 2 Degrees - 2 Degrees levation ngle in Degrees Figure 8 V-cut troug beam peak for tree zimut rotations of UT. L coordinates and vector components used. Relative mplitude in db Degrees + 2 Degrees -2 Degrees levation ngle in Degrees Figure 9 V-cuts troug te beam peak for tree zimut rotations of te UT. lpa psilon coordinates and vector components. Tese used. patterns ave used coordinates and vector components tat are te natural coice for rotation about te y-axis. Wit tis coice, te patterns sould be sifted in zimut and te sape of te patterns sould not cange. Tis is illustrated in Figure 8 were vertical cuts troug te peaks of te beams are plotted for te degree, -2 degree and +2 degree antenna orientations. Tese patterns sow excellent agreement, tat is in contrast to Figure 9 wic is a similar comparison of te V-cuts using α-ε coordinates and components. Te comparison ere is especially poor at angles far off axis. Te differences in te patterns in Figure 9 do not mean tat tere is an error in te measurement or tat it is incorrect to use te α-ε coordinates and components. ll tree curves are a correct and valid representation of te field for te given situation. Te patterns are different because te sape of te pattern canges wen using tese coordinates and components wit a rotation about te y-axis. If te sifted patterns are going to be combined, or if te sifted patterns are going to be compared and te differences used to estimate errors in te measurement, coordinates and vector components must be used wit a rotation about te y -axis. Relative mplitude in db Deg. +2 Deg. -2 Deg. rror Level levation ngle in Degrees Figure 1 Comparison of V-Cuts troug beam peak for tree rotations of UT after averaging 4 results for eac beam rotation. 7. STIMTING RRORS IN PLNR NR-FILD MSURMNTS Comparing te results of two different near-field measurements can be an effective tool for estimating errors if te measurement system is canged in a known way between measurements 2. Te cange in te measurement system is designed to identify one or more sources of error wile leaving oter sources uncanged. Rotation of te antenna about one axis can identify some sources of error tat are difficult to quantify wit oter tests as illustrated by te following examples. If te correct coordinates and components are used for a given rotation, if te rotation is precisely known, and if tere are no errors in te measurement system, te original and rotated patterns sould agree exactly. For te azimut rotations previously described, te rotations were carefully controlled and known, and te differences seen in Figure 8 are due to measurement errors. Multiple reflections between te UT and te probe produce some errors in every near-field measurement. Tis error can be identified and partially corrected by taking measurements at a series of 4 z-distances in increments of λ/8. Tis was done for all tree of te azimut beam rotations and te four far-field measurement

6 results for eac beam rotation were averaged to reduce te effect of te multiple reflections. Te average far-fields for te tree beam rotations were ten compared as sown in Figure 1 and a residual error signal calculated tat would cause te differences in te patterns. In te main beam region, were te multiple reflection error is te largest, te residual error level is approximately 5 db wile in te sidelobe region it as been reduced to approximately 6 to 65 db. Te error sources tat sould be identified by te steering of te beam in zimut are -position errors, pase linearity and room reflections in te zimut directions. From te results sown in Figure 1, te combined effect of tese error sources is less tan -6 db below te main component peak. Te beam rotation tests were repeated for levation rotations Relative mplitude in db L = Deg L = Deg. rror Signal levation ngle in Degrees Figure 12 Results of comparing veraged patterns for degrees and degrees levation beam rotations. Near-field amplitude wit Beam L = 24.5 Deg Figure 11 ntenna rotated in levation 24.5 degrees. of 8.5 and 24.5 degrees. It was not possible wit available equipment to control te rotations as precisely for tese measurements, and so te comparisons were not as good as for te zimut rotations. Te results do illustrate te identification of a different source of error as sown in Figure 12. Te large error signal of approximately -35 db for levation angles between 3 and 7 degrees is due to scattering from eiter te metal support beind te antenna or te floor. Te effect of tis scattering is evident in te nearfield data were te amplitude sows local peaks at te bottom of te scans as indicated by Figure 13. Wit tis information, additional absorber could be added beind te antenna or on te floor to furter reduce te effect of tis scattering. 8. CONCLUSIONS Four different sperical coordinate systems and te associated vector components associated wit tese coordinates ave been defined. Far-field or Near-field measurements can be presented using any of tese systems, and eac is a valid representation of te antenna pattern and polarization. If comparisons are made between different measurements or between measurements and teoretical calculations, te coordinates and components must agree. lso if te antenna is rotated about one axis and measurements are combined, te proper coordinates and components must be used tat will not cange te sape of te pattern for te rotation. mplitude (db) Figure cut -2-15near-field -1-5 amplitude for 2 beam 25 3 (in) steered 24.5 degrees in levation. 9. RFRNCS 1. C. Ludwig, Te definition of cross polarization, I Trans. ntennas Propag. Vol 21, No. 1 pp , January C. Newell, rror nalysis Tecniques for Planar Near-Field Measurements, I Trans. ntennas Propag., Vol 36, No. 6, pp , June 1988.

3.6 Directional Derivatives and the Gradient Vector

3.6 Directional Derivatives and the Gradient Vector 288 CHAPTER 3. FUNCTIONS OF SEVERAL VARIABLES 3.6 Directional Derivatives and te Gradient Vector 3.6.1 Functions of two Variables Directional Derivatives Let us first quickly review, one more time, te

More information

13.5 DIRECTIONAL DERIVATIVES and the GRADIENT VECTOR

13.5 DIRECTIONAL DERIVATIVES and the GRADIENT VECTOR 13.5 Directional Derivatives and te Gradient Vector Contemporary Calculus 1 13.5 DIRECTIONAL DERIVATIVES and te GRADIENT VECTOR Directional Derivatives In Section 13.3 te partial derivatives f x and f

More information

Chapter K. Geometric Optics. Blinn College - Physics Terry Honan

Chapter K. Geometric Optics. Blinn College - Physics Terry Honan Capter K Geometric Optics Blinn College - Pysics 2426 - Terry Honan K. - Properties of Ligt Te Speed of Ligt Te speed of ligt in a vacuum is approximately c > 3.0µ0 8 mês. Because of its most fundamental

More information

2.8 The derivative as a function

2.8 The derivative as a function CHAPTER 2. LIMITS 56 2.8 Te derivative as a function Definition. Te derivative of f(x) istefunction f (x) defined as follows f f(x + ) f(x) (x). 0 Note: tis differs from te definition in section 2.7 in

More information

MATH 5a Spring 2018 READING ASSIGNMENTS FOR CHAPTER 2

MATH 5a Spring 2018 READING ASSIGNMENTS FOR CHAPTER 2 MATH 5a Spring 2018 READING ASSIGNMENTS FOR CHAPTER 2 Note: Tere will be a very sort online reading quiz (WebWork) on eac reading assignment due one our before class on its due date. Due dates can be found

More information

Non-Interferometric Testing

Non-Interferometric Testing NonInterferometric Testing.nb Optics 513 - James C. Wyant 1 Non-Interferometric Testing Introduction In tese notes four non-interferometric tests are described: (1) te Sack-Hartmann test, (2) te Foucault

More information

More on Functions and Their Graphs

More on Functions and Their Graphs More on Functions and Teir Graps Difference Quotient ( + ) ( ) f a f a is known as te difference quotient and is used exclusively wit functions. Te objective to keep in mind is to factor te appearing in

More information

Haar Transform CS 430 Denbigh Starkey

Haar Transform CS 430 Denbigh Starkey Haar Transform CS Denbig Starkey. Background. Computing te transform. Restoring te original image from te transform 7. Producing te transform matrix 8 5. Using Haar for lossless compression 6. Using Haar

More information

VOLUMES. The volume of a cylinder is determined by multiplying the cross sectional area by the height. r h V. a) 10 mm 25 mm.

VOLUMES. The volume of a cylinder is determined by multiplying the cross sectional area by the height. r h V. a) 10 mm 25 mm. OLUME OF A CYLINDER OLUMES Te volume of a cylinder is determined by multiplying te cross sectional area by te eigt. r Were: = volume r = radius = eigt Exercise 1 Complete te table ( =.14) r a) 10 mm 5

More information

4.1 Tangent Lines. y 2 y 1 = y 2 y 1

4.1 Tangent Lines. y 2 y 1 = y 2 y 1 41 Tangent Lines Introduction Recall tat te slope of a line tells us ow fast te line rises or falls Given distinct points (x 1, y 1 ) and (x 2, y 2 ), te slope of te line troug tese two points is cange

More information

RECONSTRUCTING OF A GIVEN PIXEL S THREE- DIMENSIONAL COORDINATES GIVEN BY A PERSPECTIVE DIGITAL AERIAL PHOTOS BY APPLYING DIGITAL TERRAIN MODEL

RECONSTRUCTING OF A GIVEN PIXEL S THREE- DIMENSIONAL COORDINATES GIVEN BY A PERSPECTIVE DIGITAL AERIAL PHOTOS BY APPLYING DIGITAL TERRAIN MODEL IV. Évfolyam 3. szám - 2009. szeptember Horvát Zoltán orvat.zoltan@zmne.u REONSTRUTING OF GIVEN PIXEL S THREE- DIMENSIONL OORDINTES GIVEN Y PERSPETIVE DIGITL ERIL PHOTOS Y PPLYING DIGITL TERRIN MODEL bsztrakt/bstract

More information

Section 3. Imaging With A Thin Lens

Section 3. Imaging With A Thin Lens Section 3 Imaging Wit A Tin Lens 3- at Ininity An object at ininity produces a set o collimated set o rays entering te optical system. Consider te rays rom a inite object located on te axis. Wen te object

More information

2 The Derivative. 2.0 Introduction to Derivatives. Slopes of Tangent Lines: Graphically

2 The Derivative. 2.0 Introduction to Derivatives. Slopes of Tangent Lines: Graphically 2 Te Derivative Te two previous capters ave laid te foundation for te study of calculus. Tey provided a review of some material you will need and started to empasize te various ways we will view and use

More information

MAPI Computer Vision

MAPI Computer Vision MAPI Computer Vision Multiple View Geometry In tis module we intend to present several tecniques in te domain of te 3D vision Manuel Joao University of Mino Dep Industrial Electronics - Applications -

More information

Interference and Diffraction of Light

Interference and Diffraction of Light Interference and Diffraction of Ligt References: [1] A.P. Frenc: Vibrations and Waves, Norton Publ. 1971, Capter 8, p. 280-297 [2] PASCO Interference and Diffraction EX-9918 guide (written by Ann Hanks)

More information

Cubic smoothing spline

Cubic smoothing spline Cubic smooting spline Menu: QCExpert Regression Cubic spline e module Cubic Spline is used to fit any functional regression curve troug data wit one independent variable x and one dependent random variable

More information

4.2 The Derivative. f(x + h) f(x) lim

4.2 The Derivative. f(x + h) f(x) lim 4.2 Te Derivative Introduction In te previous section, it was sown tat if a function f as a nonvertical tangent line at a point (x, f(x)), ten its slope is given by te it f(x + ) f(x). (*) Tis is potentially

More information

, 1 1, A complex fraction is a quotient of rational expressions (including their sums) that result

, 1 1, A complex fraction is a quotient of rational expressions (including their sums) that result RT. Complex Fractions Wen working wit algebraic expressions, sometimes we come across needing to simplify expressions like tese: xx 9 xx +, xx + xx + xx, yy xx + xx + +, aa Simplifying Complex Fractions

More information

Bounding Tree Cover Number and Positive Semidefinite Zero Forcing Number

Bounding Tree Cover Number and Positive Semidefinite Zero Forcing Number Bounding Tree Cover Number and Positive Semidefinite Zero Forcing Number Sofia Burille Mentor: Micael Natanson September 15, 2014 Abstract Given a grap, G, wit a set of vertices, v, and edges, various

More information

Spherical Geometry Selection Used for Error Evaluation

Spherical Geometry Selection Used for Error Evaluation Spherical Geometry Selection Used for Error Evaluation Greg Hindman, Pat Pelland, Greg Masters Nearfield Systems Inc., Torrance, CA 952, USA ghindman@nearfield.com, ppelland@nearfield.com, gmasters@nearfield.com

More information

Piecewise Polynomial Interpolation, cont d

Piecewise Polynomial Interpolation, cont d Jim Lambers MAT 460/560 Fall Semester 2009-0 Lecture 2 Notes Tese notes correspond to Section 4 in te text Piecewise Polynomial Interpolation, cont d Constructing Cubic Splines, cont d Having determined

More information

CHAPTER 7: TRANSCENDENTAL FUNCTIONS

CHAPTER 7: TRANSCENDENTAL FUNCTIONS 7.0 Introduction and One to one Functions Contemporary Calculus 1 CHAPTER 7: TRANSCENDENTAL FUNCTIONS Introduction In te previous capters we saw ow to calculate and use te derivatives and integrals of

More information

Section 2.3: Calculating Limits using the Limit Laws

Section 2.3: Calculating Limits using the Limit Laws Section 2.3: Calculating Limits using te Limit Laws In previous sections, we used graps and numerics to approimate te value of a it if it eists. Te problem wit tis owever is tat it does not always give

More information

Linear Interpolating Splines

Linear Interpolating Splines Jim Lambers MAT 772 Fall Semester 2010-11 Lecture 17 Notes Tese notes correspond to Sections 112, 11, and 114 in te text Linear Interpolating Splines We ave seen tat ig-degree polynomial interpolation

More information

19.2 Surface Area of Prisms and Cylinders

19.2 Surface Area of Prisms and Cylinders Name Class Date 19 Surface Area of Prisms and Cylinders Essential Question: How can you find te surface area of a prism or cylinder? Resource Locker Explore Developing a Surface Area Formula Surface area

More information

( ) ( ) Mat 241 Homework Set 5 Due Professor David Schultz. x y. 9 4 The domain is the interior of the hyperbola.

( ) ( ) Mat 241 Homework Set 5 Due Professor David Schultz. x y. 9 4 The domain is the interior of the hyperbola. Mat 4 Homework Set 5 Due Professor David Scultz Directions: Sow all algebraic steps neatly and concisely using proper matematical symbolism. Wen graps and tecnology are to be implemented, do so appropriately.

More information

Tolerancing of single point diamond turned diffractive. Carl Zeiss AG, Oberkochen, Germany. with. ρ = 1/R

Tolerancing of single point diamond turned diffractive. Carl Zeiss AG, Oberkochen, Germany. with. ρ = 1/R J O U R N A L O F Journal of te European Optical Society - Rapid Publications, 0708 (007) www.jeos.org T H E E U R O P E A N Tolerancing of single point diamond turned diffractive O Poptical T elements

More information

θ R = θ 0 (1) -The refraction law says that: the direction of refracted ray (angle θ 1 from vertical) is (2)

θ R = θ 0 (1) -The refraction law says that: the direction of refracted ray (angle θ 1 from vertical) is (2) LIGHT (Basic information) - Considering te ligt of a projector in a smoky room, one gets to geometrical optics model of ligt as a set of tiny particles tat travel along straigt lines called "optical rays.

More information

MAC-CPTM Situations Project

MAC-CPTM Situations Project raft o not use witout permission -P ituations Project ituation 20: rea of Plane Figures Prompt teacer in a geometry class introduces formulas for te areas of parallelograms, trapezoids, and romi. e removes

More information

Chapter 34. Images. Two Types of Images. A Common Mirage. Plane Mirrors, Extended Object. Plane Mirrors, Point Object

Chapter 34. Images. Two Types of Images. A Common Mirage. Plane Mirrors, Extended Object. Plane Mirrors, Point Object Capter Images One o te most important uses o te basic laws governing ligt is te production o images. Images are critical to a variety o ields and industries ranging rom entertainment, security, and medicine

More information

Proceedings. Seventh ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC 2013) Palm Spring, CA

Proceedings. Seventh ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC 2013) Palm Spring, CA Proceedings Of te Sevent ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC ) Palm Spring, CA October 9 November st Parameter-Unaware Autocalibration for Occupancy Mapping David Van

More information

Vector Processing Contours

Vector Processing Contours Vector Processing Contours Andrey Kirsanov Department of Automation and Control Processes MAMI Moscow State Tecnical University Moscow, Russia AndKirsanov@yandex.ru A.Vavilin and K-H. Jo Department of

More information

MAP MOSAICKING WITH DISSIMILAR PROJECTIONS, SPATIAL RESOLUTIONS, DATA TYPES AND NUMBER OF BANDS 1. INTRODUCTION

MAP MOSAICKING WITH DISSIMILAR PROJECTIONS, SPATIAL RESOLUTIONS, DATA TYPES AND NUMBER OF BANDS 1. INTRODUCTION MP MOSICKING WITH DISSIMILR PROJECTIONS, SPTIL RESOLUTIONS, DT TYPES ND NUMBER OF BNDS Tyler J. lumbaug and Peter Bajcsy National Center for Supercomputing pplications 605 East Springfield venue, Campaign,

More information

12.2 Techniques for Evaluating Limits

12.2 Techniques for Evaluating Limits 335_qd /4/5 :5 PM Page 863 Section Tecniques for Evaluating Limits 863 Tecniques for Evaluating Limits Wat ou sould learn Use te dividing out tecnique to evaluate its of functions Use te rationalizing

More information

You should be able to visually approximate the slope of a graph. The slope m of the graph of f at the point x, f x is given by

You should be able to visually approximate the slope of a graph. The slope m of the graph of f at the point x, f x is given by Section. Te Tangent Line Problem 89 87. r 5 sin, e, 88. r sin sin Parabola 9 9 Hperbola e 9 9 9 89. 7,,,, 5 7 8 5 ortogonal 9. 5, 5,, 5, 5. Not multiples of eac oter; neiter parallel nor ortogonal 9.,,,

More information

The Euler and trapezoidal stencils to solve d d x y x = f x, y x

The Euler and trapezoidal stencils to solve d d x y x = f x, y x restart; Te Euler and trapezoidal stencils to solve d d x y x = y x Te purpose of tis workseet is to derive te tree simplest numerical stencils to solve te first order d equation y x d x = y x, and study

More information

Multi-Stack Boundary Labeling Problems

Multi-Stack Boundary Labeling Problems Multi-Stack Boundary Labeling Problems Micael A. Bekos 1, Micael Kaufmann 2, Katerina Potika 1 Antonios Symvonis 1 1 National Tecnical University of Atens, Scool of Applied Matematical & Pysical Sciences,

More information

Our Calibrated Model has No Predictive Value: An Example from the Petroleum Industry

Our Calibrated Model has No Predictive Value: An Example from the Petroleum Industry Our Calibrated Model as No Predictive Value: An Example from te Petroleum Industry J.N. Carter a, P.J. Ballester a, Z. Tavassoli a and P.R. King a a Department of Eart Sciences and Engineering, Imperial

More information

2.3 Additional Relations

2.3 Additional Relations 3 2.3 Additional Relations Figure 2.3 identiies additional relations, indicating te locations o te object and image, and te ratio o teir eigts (magniication) and orientations. Ray enters te lens parallel

More information

12.2 TECHNIQUES FOR EVALUATING LIMITS

12.2 TECHNIQUES FOR EVALUATING LIMITS Section Tecniques for Evaluating Limits 86 TECHNIQUES FOR EVALUATING LIMITS Wat ou sould learn Use te dividing out tecnique to evaluate its of functions Use te rationalizing tecnique to evaluate its of

More information

Fourth-order NMO velocity for P-waves in layered orthorhombic media vs. offset-azimuth

Fourth-order NMO velocity for P-waves in layered orthorhombic media vs. offset-azimuth Fourt-order NMO velocity for P-waves in layered orrombic media vs. set-azimut Zvi Koren* and Igor Ravve Paradigm Geopysical Summary We derive te fourt-order NMO velocity of compressional waves for a multi-layer

More information

Investigating an automated method for the sensitivity analysis of functions

Investigating an automated method for the sensitivity analysis of functions Investigating an automated metod for te sensitivity analysis of functions Sibel EKER s.eker@student.tudelft.nl Jill SLINGER j..slinger@tudelft.nl Delft University of Tecnology 2628 BX, Delft, te Neterlands

More information

Optimal In-Network Packet Aggregation Policy for Maximum Information Freshness

Optimal In-Network Packet Aggregation Policy for Maximum Information Freshness 1 Optimal In-etwork Packet Aggregation Policy for Maimum Information Fresness Alper Sinan Akyurek, Tajana Simunic Rosing Electrical and Computer Engineering, University of California, San Diego aakyurek@ucsd.edu,

More information

CESILA: Communication Circle External Square Intersection-Based WSN Localization Algorithm

CESILA: Communication Circle External Square Intersection-Based WSN Localization Algorithm Sensors & Transducers 2013 by IFSA ttp://www.sensorsportal.com CESILA: Communication Circle External Square Intersection-Based WSN Localization Algoritm Sun Hongyu, Fang Ziyi, Qu Guannan College of Computer

More information

The impact of simplified UNBab mapping function on GPS tropospheric delay

The impact of simplified UNBab mapping function on GPS tropospheric delay Te impact of simplified UNBab mapping function on GPS troposperic delay Hamza Sakidin, Tay Coo Cuan, and Asmala Amad Citation: AIP Conference Proceedings 1621, 363 (2014); doi: 10.1063/1.4898493 View online:

More information

Mean Shifting Gradient Vector Flow: An Improved External Force Field for Active Surfaces in Widefield Microscopy.

Mean Shifting Gradient Vector Flow: An Improved External Force Field for Active Surfaces in Widefield Microscopy. Mean Sifting Gradient Vector Flow: An Improved External Force Field for Active Surfaces in Widefield Microscopy. Margret Keuper Cair of Pattern Recognition and Image Processing Computer Science Department

More information

Alternating Direction Implicit Methods for FDTD Using the Dey-Mittra Embedded Boundary Method

Alternating Direction Implicit Methods for FDTD Using the Dey-Mittra Embedded Boundary Method Te Open Plasma Pysics Journal, 2010, 3, 29-35 29 Open Access Alternating Direction Implicit Metods for FDTD Using te Dey-Mittra Embedded Boundary Metod T.M. Austin *, J.R. Cary, D.N. Smite C. Nieter Tec-X

More information

You Try: A. Dilate the following figure using a scale factor of 2 with center of dilation at the origin.

You Try: A. Dilate the following figure using a scale factor of 2 with center of dilation at the origin. 1 G.SRT.1-Some Tings To Know Dilations affect te size of te pre-image. Te pre-image will enlarge or reduce by te ratio given by te scale factor. A dilation wit a scale factor of 1> x >1enlarges it. A dilation

More information

Computing geodesic paths on manifolds

Computing geodesic paths on manifolds Proc. Natl. Acad. Sci. USA Vol. 95, pp. 8431 8435, July 1998 Applied Matematics Computing geodesic pats on manifolds R. Kimmel* and J. A. Setian Department of Matematics and Lawrence Berkeley National

More information

A Cost Model for Distributed Shared Memory. Using Competitive Update. Jai-Hoon Kim Nitin H. Vaidya. Department of Computer Science

A Cost Model for Distributed Shared Memory. Using Competitive Update. Jai-Hoon Kim Nitin H. Vaidya. Department of Computer Science A Cost Model for Distributed Sared Memory Using Competitive Update Jai-Hoon Kim Nitin H. Vaidya Department of Computer Science Texas A&M University College Station, Texas, 77843-3112, USA E-mail: fjkim,vaidyag@cs.tamu.edu

More information

All truths are easy to understand once they are discovered; the point is to discover them. Galileo

All truths are easy to understand once they are discovered; the point is to discover them. Galileo Section 7. olume All truts are easy to understand once tey are discovered; te point is to discover tem. Galileo Te main topic of tis section is volume. You will specifically look at ow to find te volume

More information

Fast Calculation of Thermodynamic Properties of Water and Steam in Process Modelling using Spline Interpolation

Fast Calculation of Thermodynamic Properties of Water and Steam in Process Modelling using Spline Interpolation P R E P R N T CPWS XV Berlin, September 8, 008 Fast Calculation of Termodynamic Properties of Water and Steam in Process Modelling using Spline nterpolation Mattias Kunick a, Hans-Joacim Kretzscmar a,

More information

Communicator for Mac Quick Start Guide

Communicator for Mac Quick Start Guide Communicator for Mac Quick Start Guide 503-968-8908 sterling.net training@sterling.net Pone Support 503.968.8908, option 2 pone-support@sterling.net For te most effective support, please provide your main

More information

Holes, Knots and Shapes: A Spatial Ontology of a Puzzle

Holes, Knots and Shapes: A Spatial Ontology of a Puzzle Holes, Knots and Sapes: A Spatial Ontology of a Puzzle Paulo Santos Centro Universitário da FEI, São Paulo, email: psantos@fei.edu.br Pedro Cabalar Coruña University, Spain, email: cabalar@dc.fi.udc.es

More information

Proceedings of the 8th WSEAS International Conference on Neural Networks, Vancouver, British Columbia, Canada, June 19-21,

Proceedings of the 8th WSEAS International Conference on Neural Networks, Vancouver, British Columbia, Canada, June 19-21, Proceedings of te 8t WSEAS International Conference on Neural Networks, Vancouver, Britis Columbia, Canada, June 9-2, 2007 3 Neural Network Structures wit Constant Weigts to Implement Dis-Jointly Removed

More information

Engineering Mechanics (Statics) (Centroid) Dr. Hayder A. Mehdi

Engineering Mechanics (Statics) (Centroid) Dr. Hayder A. Mehdi Engineering Mecanics (Statics) (Centroid) Dr. Hader A. Medi Centroid of an Area: If an area lies in te x plane and is ounded te curve = f (x), as sown in te following figure ten its centroid will e in

More information

Effect of GPS Tropospheric Delay Neill Mapping Function Simplification

Effect of GPS Tropospheric Delay Neill Mapping Function Simplification Malaysian Journal of Matematical Sciences 3(1): 95-107 (2009) Effect of GPS Troposperic Delay Neill Mapping Function Simplification 1 Hamza Sakidin, 1 Mod Rizam Abu Bakar, 2 Abdul Rasid Moamed Sariff,

More information

THANK YOU FOR YOUR PURCHASE!

THANK YOU FOR YOUR PURCHASE! THANK YOU FOR YOUR PURCHASE! Te resources included in tis purcase were designed and created by me. I ope tat you find tis resource elpful in your classroom. Please feel free to contact me wit any questions

More information

NOTES: A quick overview of 2-D geometry

NOTES: A quick overview of 2-D geometry NOTES: A quick overview of 2-D geometry Wat is 2-D geometry? Also called plane geometry, it s te geometry tat deals wit two dimensional sapes flat tings tat ave lengt and widt, suc as a piece of paper.

More information

2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media,

2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 016 IEEE. Personal use of tis material is permitted. Permission from IEEE must be obtained for all oter uses, in any current or future media, including reprinting/republising tis material for advertising

More information

Classify solids. Find volumes of prisms and cylinders.

Classify solids. Find volumes of prisms and cylinders. 11.4 Volumes of Prisms and Cylinders Essential Question How can you find te volume of a prism or cylinder tat is not a rigt prism or rigt cylinder? Recall tat te volume V of a rigt prism or a rigt cylinder

More information

PLK-B SERIES Technical Manual (USA Version) CLICK HERE FOR CONTENTS

PLK-B SERIES Technical Manual (USA Version) CLICK HERE FOR CONTENTS PLK-B SERIES Technical Manual (USA Version) CLICK ERE FOR CONTENTS CONTROL BOX PANEL MOST COMMONLY USED FUNCTIONS INITIAL READING OF SYSTEM SOFTWARE/PAGES 1-2 RE-INSTALLATION OF TE SYSTEM SOFTWARE/PAGES

More information

SUPER OBLIQUE INCIDENCE INTERFEROMETER USING SWS PRISM

SUPER OBLIQUE INCIDENCE INTERFEROMETER USING SWS PRISM SUPER OBLIQUE INCIDENCE INTERFEROMETER USING SWS PRISM Yukitosi OTANI 1,2), Yasuiro MIZUTANI 2), Noriiro UMEDA 2) 1) Optical Sciences Center, University of Arizona, Arizona 85721 2) Dept, of Mec. Sys.

More information

On the use of FHT, its modification for practical applications and the structure of Hough image

On the use of FHT, its modification for practical applications and the structure of Hough image On te use of FHT, its modification for practical applications and te structure of Houg image M. Aliev 1,3, E.I. Ersov, D.P. Nikolaev,3 1 Federal Researc Center Computer Science and Control of Russian Academy

More information

Local features and image matching May 8 th, 2018

Local features and image matching May 8 th, 2018 Local features and image matcing May 8 t, 2018 Yong Jae Lee UC Davis Last time RANSAC for robust fitting Lines, translation Image mosaics Fitting a 2D transformation Homograpy 2 Today Mosaics recap: How

More information

Materials: Whiteboard, TI-Nspire classroom set, quadratic tangents program, and a computer projector.

Materials: Whiteboard, TI-Nspire classroom set, quadratic tangents program, and a computer projector. Adam Clinc Lesson: Deriving te Derivative Grade Level: 12 t grade, Calculus I class Materials: Witeboard, TI-Nspire classroom set, quadratic tangents program, and a computer projector. Goals/Objectives:

More information

Hash-Based Indexes. Chapter 11. Comp 521 Files and Databases Spring

Hash-Based Indexes. Chapter 11. Comp 521 Files and Databases Spring Has-Based Indexes Capter 11 Comp 521 Files and Databases Spring 2010 1 Introduction As for any index, 3 alternatives for data entries k*: Data record wit key value k

More information

Section 1.2 The Slope of a Tangent

Section 1.2 The Slope of a Tangent Section 1.2 Te Slope of a Tangent You are familiar wit te concept of a tangent to a curve. Wat geometric interpretation can be given to a tangent to te grap of a function at a point? A tangent is te straigt

More information

Density Estimation Over Data Stream

Density Estimation Over Data Stream Density Estimation Over Data Stream Aoying Zou Dept. of Computer Science, Fudan University 22 Handan Rd. Sangai, 2433, P.R. Cina ayzou@fudan.edu.cn Ziyuan Cai Dept. of Computer Science, Fudan University

More information

15-122: Principles of Imperative Computation, Summer 2011 Assignment 6: Trees and Secret Codes

15-122: Principles of Imperative Computation, Summer 2011 Assignment 6: Trees and Secret Codes 15-122: Principles of Imperative Computation, Summer 2011 Assignment 6: Trees and Secret Codes William Lovas (wlovas@cs) Karl Naden Out: Tuesday, Friday, June 10, 2011 Due: Monday, June 13, 2011 (Written

More information

Symmetric Tree Replication Protocol for Efficient Distributed Storage System*

Symmetric Tree Replication Protocol for Efficient Distributed Storage System* ymmetric Tree Replication Protocol for Efficient Distributed torage ystem* ung Cune Coi 1, Hee Yong Youn 1, and Joong up Coi 2 1 cool of Information and Communications Engineering ungkyunkwan University

More information

EXERCISES 6.1. Cross-Sectional Areas. 6.1 Volumes by Slicing and Rotation About an Axis 405

EXERCISES 6.1. Cross-Sectional Areas. 6.1 Volumes by Slicing and Rotation About an Axis 405 6. Volumes b Slicing and Rotation About an Ais 5 EXERCISES 6. Cross-Sectional Areas In Eercises and, find a formula for te area A() of te crosssections of te solid perpendicular to te -ais.. Te solid lies

More information

wrobot k wwrobot hrobot (a) Observation area Horopter h(θ) (Virtual) horopters h(θ+ θ lim) U r U l h(θ+ θ) Base line Left camera Optical axis

wrobot k wwrobot hrobot (a) Observation area Horopter h(θ) (Virtual) horopters h(θ+ θ lim) U r U l h(θ+ θ) Base line Left camera Optical axis Selective Acquisition of 3-D Information Enoug for Finding Passable Free Spaces Using an Active Stereo Vision System Atsusi Nisikawa, Atsusi Okubo, and Fumio Miyazaki Department of Systems and Human Science

More information

2D transformations Homogeneous coordinates. Uses of Transformations

2D transformations Homogeneous coordinates. Uses of Transformations 2D transformations omogeneous coordinates Uses of Transformations Modeling: position and resize parts of a complex model; Viewing: define and position te virtual camera Animation: define ow objects move/cange

More information

Tilings of rectangles with T-tetrominoes

Tilings of rectangles with T-tetrominoes Tilings of rectangles wit T-tetrominoes Micael Korn and Igor Pak Department of Matematics Massacusetts Institute of Tecnology Cambridge, MA, 2139 mikekorn@mit.edu, pak@mat.mit.edu August 26, 23 Abstract

More information

ANTENNA ALIGNMENT IN A NEAR-FIELD FACILITY

ANTENNA ALIGNMENT IN A NEAR-FIELD FACILITY ANTENNA ALIGNMENT IN A NEAR-FIELD FACILITY Mart Hagenbeek and Arnold R.Boomstra Naval Maintenance Establishment, Division SEWACO Royal Netherlands Navy, P.O.Box 10 000, 1780 CA Den Helder, The Netherlands.

More information

CRASHWORTHINESS ASSESSMENT IN AIRCRAFT DITCHING INCIDENTS

CRASHWORTHINESS ASSESSMENT IN AIRCRAFT DITCHING INCIDENTS 27 TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES CRASHWORTHINESS ASSESSMENT IN AIRCRAFT DITCHING INCIDENTS C. Candra*, T. Y. Wong* and J. Bayandor** * Te Sir Lawrence Wackett Aerospace Centre

More information

Redundancy Awareness in SQL Queries

Redundancy Awareness in SQL Queries Redundancy Awareness in QL Queries Bin ao and Antonio Badia omputer Engineering and omputer cience Department University of Louisville bin.cao,abadia @louisville.edu Abstract In tis paper, we study QL

More information

Traffic Pattern-based Adaptive Routing for Intra-group Communication in Dragonfly Networks

Traffic Pattern-based Adaptive Routing for Intra-group Communication in Dragonfly Networks Traffic Pattern-based Adaptive Routing for Intra-group Communication in Dragonfly Networks Peyman Faizian, Md Safayat Raman, Md Atiqul Molla, Xin Yuan Department of Computer Science Florida State University

More information

Haptic Rendering of Topological Constraints to Users Manipulating Serial Virtual Linkages

Haptic Rendering of Topological Constraints to Users Manipulating Serial Virtual Linkages Haptic Rendering of Topological Constraints to Users Manipulating Serial Virtual Linkages Daniela Constantinescu and Septimiu E Salcudean Electrical & Computer Engineering Department University of Britis

More information

Robotics and Autonomous Systems. Joint origin identification of articulated robots with marker-based multi-camera optical tracking systems

Robotics and Autonomous Systems. Joint origin identification of articulated robots with marker-based multi-camera optical tracking systems Robotics and Autonomous Systems 61 (2013) 580 592 Contents lists available at SciVerse ScienceDirect Robotics and Autonomous Systems journal omepage: wwwelseviercom/locate/robot Joint origin identification

More information

An Algorithm for Loopless Deflection in Photonic Packet-Switched Networks

An Algorithm for Loopless Deflection in Photonic Packet-Switched Networks An Algoritm for Loopless Deflection in Potonic Packet-Switced Networks Jason P. Jue Center for Advanced Telecommunications Systems and Services Te University of Texas at Dallas Ricardson, TX 75083-0688

More information

Notes: Dimensional Analysis / Conversions

Notes: Dimensional Analysis / Conversions Wat is a unit system? A unit system is a metod of taking a measurement. Simple as tat. We ave units for distance, time, temperature, pressure, energy, mass, and many more. Wy is it important to ave a standard?

More information

An Anchor Chain Scheme for IP Mobility Management

An Anchor Chain Scheme for IP Mobility Management An Ancor Cain Sceme for IP Mobility Management Yigal Bejerano and Israel Cidon Department of Electrical Engineering Tecnion - Israel Institute of Tecnology Haifa 32000, Israel E-mail: bej@tx.tecnion.ac.il.

More information

Measuring Length 11and Area

Measuring Length 11and Area Measuring Lengt 11and Area 11.1 Areas of Triangles and Parallelograms 11.2 Areas of Trapezoids, Romuses, and Kites 11.3 Perimeter and Area of Similar Figures 11.4 Circumference and Arc Lengt 11.5 Areas

More information

12.2 Investigate Surface Area

12.2 Investigate Surface Area Investigating g Geometry ACTIVITY Use before Lesson 12.2 12.2 Investigate Surface Area MATERIALS grap paper scissors tape Q U E S T I O N How can you find te surface area of a polyedron? A net is a pattern

More information

Mean Waiting Time Analysis in Finite Storage Queues for Wireless Cellular Networks

Mean Waiting Time Analysis in Finite Storage Queues for Wireless Cellular Networks Mean Waiting Time Analysis in Finite Storage ueues for Wireless ellular Networks J. YLARINOS, S. LOUVROS, K. IOANNOU, A. IOANNOU 3 A.GARMIS 2 and S.KOTSOOULOS Wireless Telecommunication Laboratory, Department

More information

The navigability variable is binary either a cell is navigable or not. Thus, we can invert the entire reasoning by substituting x i for x i : (4)

The navigability variable is binary either a cell is navigable or not. Thus, we can invert the entire reasoning by substituting x i for x i : (4) A Multi-Resolution Pyramid for Outdoor Robot Terrain Perception Micael Montemerlo and Sebastian Trun AI Lab, Stanford University 353 Serra Mall Stanford, CA 94305-9010 {mmde,trun}@stanford.edu Abstract

More information

Parallel Simulation of Equation-Based Models on CUDA-Enabled GPUs

Parallel Simulation of Equation-Based Models on CUDA-Enabled GPUs Parallel Simulation of Equation-Based Models on CUDA-Enabled GPUs Per Ostlund Department of Computer and Information Science Linkoping University SE-58183 Linkoping, Sweden per.ostlund@liu.se Kristian

More information

Some Handwritten Signature Parameters in Biometric Recognition Process

Some Handwritten Signature Parameters in Biometric Recognition Process Some Handwritten Signature Parameters in Biometric Recognition Process Piotr Porwik Institute of Informatics, Silesian Uniersity, Bdziska 39, 41- Sosnowiec, Poland porwik@us.edu.pl Tomasz Para Institute

More information

Intra- and Inter-Session Network Coding in Wireless Networks

Intra- and Inter-Session Network Coding in Wireless Networks Intra- and Inter-Session Network Coding in Wireless Networks Hulya Seferoglu, Member, IEEE, Atina Markopoulou, Member, IEEE, K K Ramakrisnan, Fellow, IEEE arxiv:857v [csni] 3 Feb Abstract In tis paper,

More information

On the Use of Radio Resource Tests in Wireless ad hoc Networks

On the Use of Radio Resource Tests in Wireless ad hoc Networks Tecnical Report RT/29/2009 On te Use of Radio Resource Tests in Wireless ad oc Networks Diogo Mónica diogo.monica@gsd.inesc-id.pt João Leitão jleitao@gsd.inesc-id.pt Luis Rodrigues ler@ist.utl.pt Carlos

More information

Overcomplete Steerable Pyramid Filters and Rotation Invariance

Overcomplete Steerable Pyramid Filters and Rotation Invariance vercomplete Steerable Pyramid Filters and Rotation Invariance H. Greenspan, S. Belongie R. Goodman and P. Perona S. Raksit and C. H. Anderson Department of Electrical Engineering Department of Anatomy

More information

Pedestrian Detection Algorithm for On-board Cameras of Multi View Angles

Pedestrian Detection Algorithm for On-board Cameras of Multi View Angles Pedestrian Detection Algoritm for On-board Cameras of Multi View Angles S. Kamijo IEEE, K. Fujimura, and Y. Sibayama Abstract In tis paper, a general algoritm for pedestrian detection by on-board monocular

More information

Follow this and additional works at: Part of the Geology Commons

Follow this and additional works at:  Part of the Geology Commons University of Wyoming Wyoming Scolars Repository Geology and Geopysics Faculty Publications Geology and Geopysics 5-1-2011 An Accurate Ray-Based Offset-To-Angle Transform from Normal Moveout Uncorrected

More information

Numerical Derivatives

Numerical Derivatives Lab 15 Numerical Derivatives Lab Objective: Understand and implement finite difference approximations of te derivative in single and multiple dimensions. Evaluate te accuracy of tese approximations. Ten

More information

AVL Trees Outline and Required Reading: AVL Trees ( 11.2) CSE 2011, Winter 2017 Instructor: N. Vlajic

AVL Trees Outline and Required Reading: AVL Trees ( 11.2) CSE 2011, Winter 2017 Instructor: N. Vlajic 1 AVL Trees Outline and Required Reading: AVL Trees ( 11.2) CSE 2011, Winter 2017 Instructor: N. Vlajic AVL Trees 2 Binary Searc Trees better tan linear dictionaries; owever, te worst case performance

More information

Protecting Storage Location Privacy in Sensor Networks

Protecting Storage Location Privacy in Sensor Networks Protecting Storage Location Privacy in Sensor Networks Jianming Zou, Wenseng Zang, and Daji Qiao Iowa State University Ames, IA 511 Email: {jmzou,wzang,daji}@iastate.edu ASTAT Numerous scemes ave been

More information

CE 221 Data Structures and Algorithms

CE 221 Data Structures and Algorithms CE Data Structures and Algoritms Capter 4: Trees (AVL Trees) Text: Read Weiss, 4.4 Izmir University of Economics AVL Trees An AVL (Adelson-Velskii and Landis) tree is a binary searc tree wit a balance

More information

Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art

Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art Multi-Objective Particle Swarm Optimizers: A Survey of te State-of-te-Art Margarita Reyes-Sierra and Carlos A. Coello Coello CINVESTAV-IPN (Evolutionary Computation Group) Electrical Engineering Department,

More information