1.4 Application Separable Equations and the Logistic Equation

Size: px
Start display at page:

Download "1.4 Application Separable Equations and the Logistic Equation"

Transcription

1 1.4 Applicaion Separable Equaions and he Logisic Equaion If a separable differenial equaion is wrien in he form f ( y) dy= g( x) dx, hen is general soluion can be wrien in he form f ( y ) dy = g ( x ) dx + C. Thus he soluion of a separable differenial equaion reduces o he evaluaion of wo indefinie inegrals. Hence i is emping o use a compuer algebra sysem such as Maple or Mahemaica ha can compue such inegrals symbolically. We illusrae his approach using he logisic differenial equaion dx d 2 = ax bx (1) ha models a populaion x() wih birhs (per uni of ime) proporional o x and deahs proporional o x 2. If a = 0.01 and b = , for insance, Eq. (1) is dx d x = 0.01x x = (100 x). (2) Separaion of variables leads o dx d = C x(100 x) = +. (3) Any compuer algebra sysem gives a resul of he form ln( x) ( x 100) = + C. (4) You can now apply he iniial condiion x(0) = x0, combine logarihms, and finally exponeniae in order o solve (4) for he paricular soluion x () = 100 xe 100 x x0e (5) of (2). The direcion field and soluion curves shown in Fig in he ex sugges ha, whaever is he iniial value x 0, he soluion x ( ) 100 as. Can you use (5) o verify his conjecure? 12 Chaper 1

2 The secions ha follow illusrae he use of Maple, Mahemaica, and MATLAB o carry ou he procedure oulined above. You migh warm up for he invesigaion below by applying a compuer algebra sysem o solve Problems 1 28 in Secion 1.4 of he ex. Invesigaion For your own personal logisic equaion, ake a = m/n and b = 1/n in (1), wih m and n being he larges wo disinc digis (in eiher order) in you suden ID number. (i) Firs generae a slope field for your differenial equaion and include a sufficien number of soluion curves ha you can see wha happens o he populaion as. Sae your inference plainly. (ii) Nex, use a compuer algebra sysem o solve he differenial equaion symbolically, and use he symbolic soluion o find he limi of x() as. Was your graphically-based inference correc? (iii) Finally, sae and solve a numerical problem using he symbolic soluion. For insance, how long does i ake x o grow from a seleced iniial value x 0 o a given arge value x 1? Using Maple Firs we inegrae boh sides of our separaed differenial equaion as in Eq. (3). soln := in(1/(x*(100-x)),x) = in(1/10000,)+c; soln : = ln( x) ln( x) = in(1/10000, ) + C Then we apply he iniial condiion x(0) = x0 o find he consan C. C := solve(subs(x=x0,=0,soln),c); We subsiue his value of C and simplify. C : = ln( x0) ln( x0) soln := simplify(100*soln); 1 soln : = ln( x) ln( x) = + ln( x0) ln( x0) 100 Nex we exponeniae boh sides of his equaion. 1.4 Applicaion 13

3 soln := simplify(exp(lhs(%)) = exp(rhs(%))); soln x e x0 : = = x x0 x() = solve(soln, x); Using Mahemaica e x0 x ( ) = x0 + e x0 Firs we inegrae boh sides of our separaed differenial equaion as in Eq. (3). Inegrae[1/(x(100-x)),x] == Inegrae[1/10000,] + c log( x) 1 log( x 100) == c Then we apply he iniial condiion x(0) = x0 o find he consan c. c = Firs[ soln /. {->0, x->x0} ] log( x0) 1 log( x 0 100) We subsiue his value of c and simplify. Expand[100*Firs[soln]] == Expand[100*Las[soln]] 1 log( x) log( x 100) == log( x0 100) + log( x0) Nex we exponeniae boh sides of his equaion. 14 Chaper 1

4 Exp[Firs[soln]] == Exp[Las[soln]] // Simplify x e /100 x0 == x 100 x0 100 Solve[ soln, x ]; x e x0 e x x x = Firs[x /. soln] 100e x0 e x0 x Using MATLAB Here we solve he logisic equaion in (2) using he MATLAB "symbolic oolbox" inerface o he Maple kernel. We begin by separaing variables and inegraing each side of he resuling equaion. However, i is more convenien now o work wih "everyhing on one side of he equaion", as in dx d C x(100 x) = So we sar by "declaring" our symbolic variables and evaluaing he wo inegrals in his equaion. syms x C in(1/(x*(100-x)),x) - in(1/10000, ) - C 1/100*log(x)-1/100*log(-100+x)-1/10000*-C We are acually hinking here of he equaion 0, bu he righ-hand side zero is suppressed hroughou. I simplifies he equaion a bi by muliplying hrough by *soln log(x)-log(-100+x)-1/100*-100*c 1.4 Applicaion 15

5 Then we apply he iniial condiion x(0) = x0 o find he consan C. soln0 = subs(soln, {,x}, {0,'x0'}) soln0 = log(x0)-log(-100+x0)-100*c C = solve(soln0, C) C = 1/100*log(x0)-1/100*log(-100+x0) We subsiue his value of C simply by evaluaing he presen implici soluion. eval(soln) log(x)-log(-100+x)-1/100*-log(x0)+log(-100+x0) x = solve(soln, x); prey(x) x0 exp(1/100 ) x0 + x0 exp(1/100 ) 16 Chaper 1

MATH Differential Equations September 15, 2008 Project 1, Fall 2008 Due: September 24, 2008

MATH Differential Equations September 15, 2008 Project 1, Fall 2008 Due: September 24, 2008 MATH 5 - Differenial Equaions Sepember 15, 8 Projec 1, Fall 8 Due: Sepember 4, 8 Lab 1.3 - Logisics Populaion Models wih Harvesing For his projec we consider lab 1.3 of Differenial Equaions pages 146 o

More information

It is easier to visualize plotting the curves of cos x and e x separately: > plot({cos(x),exp(x)},x = -5*Pi..Pi,y = );

It is easier to visualize plotting the curves of cos x and e x separately: > plot({cos(x),exp(x)},x = -5*Pi..Pi,y = ); Mah 467 Homework Se : some soluions > wih(deools): wih(plos): Warning, he name changecoords has been redefined Problem :..7 Find he fixed poins, deermine heir sabiliy, for x( ) = cos x e x > plo(cos(x)

More information

Project #1 Math 285 Name:

Project #1 Math 285 Name: Projec #1 Mah 85 Name: Solving Orinary Differenial Equaions by Maple: Sep 1: Iniialize he program: wih(deools): wih(pdeools): Sep : Define an ODE: (There are several ways of efining equaions, we sar wih

More information

FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS

FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS Mohammed A. Aseeri and M. I. Sobhy Deparmen of Elecronics, The Universiy of Ken a Canerbury Canerbury, Ken, CT2

More information

the marginal product. Using the rule for differentiating a power function,

the marginal product. Using the rule for differentiating a power function, 3 Augu 07 Chaper 3 Derivaive ha economi ue 3 Rule for differeniaion The chain rule Economi ofen work wih funcion of variable ha are hemelve funcion of oher variable For example, conider a monopoly elling

More information

Gauss-Jordan Algorithm

Gauss-Jordan Algorithm Gauss-Jordan Algorihm The Gauss-Jordan algorihm is a sep by sep procedure for solving a sysem of linear equaions which may conain any number of variables and any number of equaions. The algorihm is carried

More information

Engineering Mathematics 2018

Engineering Mathematics 2018 Engineering Mahemaics 08 SUBJET NAME : Mahemaics II SUBJET ODE : MA65 MATERIAL NAME : Par A quesions REGULATION : R03 UPDATED ON : November 06 TEXTBOOK FOR REFERENE To buy he book visi : Sri Hariganesh

More information

Numerical Solution of ODE

Numerical Solution of ODE Numerical Soluion of ODE Euler and Implici Euler resar; wih(deools): wih(plos): The package ploools conains more funcions for ploing, especially a funcion o draw a single line: wih(ploools): wih(linearalgebra):

More information

NEWTON S SECOND LAW OF MOTION

NEWTON S SECOND LAW OF MOTION Course and Secion Dae Names NEWTON S SECOND LAW OF MOTION The acceleraion of an objec is defined as he rae of change of elociy. If he elociy changes by an amoun in a ime, hen he aerage acceleraion during

More information

Fill in the following table for the functions shown below.

Fill in the following table for the functions shown below. By: Carl H. Durney and Neil E. Coer Example 1 EX: Fill in he following able for he funcions shown below. he funcion is odd he funcion is even he funcion has shif-flip symmery he funcion has quarer-wave

More information

Why not experiment with the system itself? Ways to study a system System. Application areas. Different kinds of systems

Why not experiment with the system itself? Ways to study a system System. Application areas. Different kinds of systems Simulaion Wha is simulaion? Simple synonym: imiaion We are ineresed in sudying a Insead of experimening wih he iself we experimen wih a model of he Experimen wih he Acual Ways o sudy a Sysem Experimen

More information

Sam knows that his MP3 player has 40% of its battery life left and that the battery charges by an additional 12 percentage points every 15 minutes.

Sam knows that his MP3 player has 40% of its battery life left and that the battery charges by an additional 12 percentage points every 15 minutes. 8.F Baery Charging Task Sam wans o ake his MP3 player and his video game player on a car rip. An hour before hey plan o leave, he realized ha he forgo o charge he baeries las nigh. A ha poin, he plugged

More information

Mass-Spring Systems and Resonance

Mass-Spring Systems and Resonance Mass-Spring Sysems and Resonance Comparing he effecs of damping coefficiens An ineresing problem is o compare he he effec of differen values of he damping coefficien c on he resuling moion of he mass on

More information

4.1 3D GEOMETRIC TRANSFORMATIONS

4.1 3D GEOMETRIC TRANSFORMATIONS MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- Dep. of Compuer Science And Applicaions, SJCET, Palai 94 4. 3D GEOMETRIC TRANSFORMATIONS Mehods for geomeric ransformaions and objec modeling in hree dimensions

More information

Matlab5 5.3 symbolisches Lösen von DGLn

Matlab5 5.3 symbolisches Lösen von DGLn C:\Si5\Ingmah\symbmalab\DGLn_N4_2.doc, Seie /5 Prof. Dr. R. Kessler, Homepage: hp://www.home.hs-karlsruhe.de/~kero/ Malab5 5.3 symbolisches Lösen von DGLn % Beispiele aus Malab 4.3 Suden Ediion Handbuch

More information

Motor Control. 5. Control. Motor Control. Motor Control

Motor Control. 5. Control. Motor Control. Motor Control 5. Conrol In his chaper we will do: Feedback Conrol On/Off Conroller PID Conroller Moor Conrol Why use conrol a all? Correc or wrong? Supplying a cerain volage / pulsewidh will make he moor spin a a cerain

More information

MOTION DETECTORS GRAPH MATCHING LAB PRE-LAB QUESTIONS

MOTION DETECTORS GRAPH MATCHING LAB PRE-LAB QUESTIONS NME: TE: LOK: MOTION ETETORS GRPH MTHING L PRE-L QUESTIONS 1. Read he insrucions, and answer he following quesions. Make sure you resae he quesion so I don hae o read he quesion o undersand he answer..

More information

1 œ DRUM SET KEY. 8 Odd Meter Clave Conor Guilfoyle. Cowbell (neck) Cymbal. Hi-hat. Floor tom (shell) Clave block. Cowbell (mouth) Hi tom.

1 œ DRUM SET KEY. 8 Odd Meter Clave Conor Guilfoyle. Cowbell (neck) Cymbal. Hi-hat. Floor tom (shell) Clave block. Cowbell (mouth) Hi tom. DRUM SET KEY Hi-ha Cmbal Clave block Cowbell (mouh) 0 Cowbell (neck) Floor om (shell) Hi om Mid om Snare Floor om Snare cross sick or clave block Bass drum Hi-ha wih foo 8 Odd Meer Clave Conor Guilfole

More information

Quantitative macro models feature an infinite number of periods A more realistic (?) view of time

Quantitative macro models feature an infinite number of periods A more realistic (?) view of time INFINIE-HORIZON CONSUMPION-SAVINGS MODEL SEPEMBER, Inroducion BASICS Quaniaive macro models feaure an infinie number of periods A more realisic (?) view of ime Infinie number of periods A meaphor for many

More information

STRING DESCRIPTIONS OF DATA FOR DISPLAY*

STRING DESCRIPTIONS OF DATA FOR DISPLAY* SLAC-PUB-383 January 1968 STRING DESCRIPTIONS OF DATA FOR DISPLAY* J. E. George and W. F. Miller Compuer Science Deparmen and Sanford Linear Acceleraor Cener Sanford Universiy Sanford, California Absrac

More information

Motion along a Line. Describing Motion along a Line

Motion along a Line. Describing Motion along a Line Moion along a Line Describing Moion: Displacemen Velociy Acceleraion Uniformly Acceleraed Moion Free Fall Describing Moion along a Line Wha is he posiion, elociy, and acceleraion of he blue do a each insan

More information

Integro-differential splines and quadratic formulae

Integro-differential splines and quadratic formulae Inegro-differenial splines and quadraic formulae I.G. BUROVA, O. V. RODNIKOVA S. Peersburg Sae Universiy 7/9 Universiesaya nab., S.Persburg, 9934 Russia i.g.burova@spbu.ru, burovaig@mail.ru Absrac: This

More information

DEFINITION OF THE LAPLACE TRANSFORM

DEFINITION OF THE LAPLACE TRANSFORM 74 CHAPER 7 HE LAPLACE RANSFORM 7 DEFINIION OF HE LAPLACE RANSFORM REVIEW MAERIAL Improper inegral wih infinie limi of inegraio Inegraion y par and parial fracion decompoiion INRODUCION In elemenary calculu

More information

Learning in Games via Opponent Strategy Estimation and Policy Search

Learning in Games via Opponent Strategy Estimation and Policy Search Learning in Games via Opponen Sraegy Esimaion and Policy Search Yavar Naddaf Deparmen of Compuer Science Universiy of Briish Columbia Vancouver, BC yavar@naddaf.name Nando de Freias (Supervisor) Deparmen

More information

CENG 477 Introduction to Computer Graphics. Modeling Transformations

CENG 477 Introduction to Computer Graphics. Modeling Transformations CENG 477 Inroducion o Compuer Graphics Modeling Transformaions Modeling Transformaions Model coordinaes o World coordinaes: Model coordinaes: All shapes wih heir local coordinaes and sies. world World

More information

COSC 3213: Computer Networks I Chapter 6 Handout # 7

COSC 3213: Computer Networks I Chapter 6 Handout # 7 COSC 3213: Compuer Neworks I Chaper 6 Handou # 7 Insrucor: Dr. Marvin Mandelbaum Deparmen of Compuer Science York Universiy F05 Secion A Medium Access Conrol (MAC) Topics: 1. Muliple Access Communicaions:

More information

Implementing Ray Casting in Tetrahedral Meshes with Programmable Graphics Hardware (Technical Report)

Implementing Ray Casting in Tetrahedral Meshes with Programmable Graphics Hardware (Technical Report) Implemening Ray Casing in Terahedral Meshes wih Programmable Graphics Hardware (Technical Repor) Marin Kraus, Thomas Erl March 28, 2002 1 Inroducion Alhough cell-projecion, e.g., [3, 2], and resampling,

More information

REDUCTIONS BBM ALGORITHMS DEPT. OF COMPUTER ENGINEERING ERKUT ERDEM. Bird s-eye view. May. 12, Reduction.

REDUCTIONS BBM ALGORITHMS DEPT. OF COMPUTER ENGINEERING ERKUT ERDEM. Bird s-eye view. May. 12, Reduction. BBM 0 - ALGORITHMS DEPT. OF COMPUTER ENGINEERING ERKUT ERDEM REDUCTIONS May., 0 Bird s-eye view Desideraa. Classify problems according o compuaional requiremens. complexiy order of growh examples linear

More information

STEREO PLANE MATCHING TECHNIQUE

STEREO PLANE MATCHING TECHNIQUE STEREO PLANE MATCHING TECHNIQUE Commission III KEY WORDS: Sereo Maching, Surface Modeling, Projecive Transformaion, Homography ABSTRACT: This paper presens a new ype of sereo maching algorihm called Sereo

More information

The Laplace Transform

The Laplace Transform 7 he Laplace ranform 7 Definiion of he Laplace ranform 7 Invere ranform and ranform of Derivaive 7 Invere ranform 7 ranform of Derivaive 73 Operaional Properie I 73 ranlaion on he -Axi 73 ranlaion on he

More information

Assignment 2. Due Monday Feb. 12, 10:00pm.

Assignment 2. Due Monday Feb. 12, 10:00pm. Faculy of rs and Science Universiy of Torono CSC 358 - Inroducion o Compuer Neworks, Winer 218, LEC11 ssignmen 2 Due Monday Feb. 12, 1:pm. 1 Quesion 1 (2 Poins): Go-ack n RQ In his quesion, we review how

More information

Chapter Six Chapter Six

Chapter Six Chapter Six Chaper Si Chaper Si 0 CHAPTER SIX ConcepTess and Answers and Commens for Secion.. Which of he following graphs (a) (d) could represen an aniderivaive of he funcion shown in Figure.? Figure. (a) (b) (c)

More information

Boyce - DiPrima 8.4, Multistep Methods

Boyce - DiPrima 8.4, Multistep Methods Boyce - DiPrima 8., Mulisep Mehods Secion 8., p. 67: Iniializaion In[1]:= In[]:= Impor "ColorNames.m" DiffEqs` Runga-Kua Mehod Implemen one sep of he Runge-Kua Mehod. In[]:= Clear y,, h, f ; eqn : y' f,

More information

ME 406 Assignment #1 Solutions

ME 406 Assignment #1 Solutions Assignmen#1Sol.nb 1 ME 406 Assignmen #1 Soluions PROBLEM 1 We define he funcion for Mahemaica. In[1]:= f@_d := Ep@D - 4 Sin@D (a) We use Plo o consruc he plo. In[2]:= Plo@f@D, 8, -5, 5

More information

Y. Tsiatouhas. VLSI Systems and Computer Architecture Lab

Y. Tsiatouhas. VLSI Systems and Computer Architecture Lab CMOS INEGRAED CIRCUI DESIGN ECHNIQUES Universiy of Ioannina Clocking Schemes Dep. of Compuer Science and Engineering Y. siaouhas CMOS Inegraed Circui Design echniques Overview 1. Jier Skew hroughpu Laency

More information

Wiley Plus. Assignment 1 is online:

Wiley Plus. Assignment 1 is online: Wile Plus Assignmen 1 is online: 6 problems from chapers and 3 1D and D Kinemaics Due Monda Ocober 5 Before 11 pm! Chaper II: Kinemaics In One Dimension Displacemen Speed and Veloci Acceleraion Equaions

More information

Scattering at an Interface: Normal Incidence

Scattering at an Interface: Normal Incidence Course Insrucor Dr. Raymond C. Rumpf Office: A 337 Phone: (915) 747 6958 Mail: rcrumpf@uep.edu 4347 Applied lecromagneics Topic 3f Scaering a an Inerface: Normal Incidence Scaering These Normal noes Incidence

More information

COMP26120: Algorithms and Imperative Programming

COMP26120: Algorithms and Imperative Programming COMP26120 ecure C3 1/48 COMP26120: Algorihms and Imperaive Programming ecure C3: C - Recursive Daa Srucures Pee Jinks School of Compuer Science, Universiy of Mancheser Auumn 2011 COMP26120 ecure C3 2/48

More information

The Roots of Lisp paul graham

The Roots of Lisp paul graham The Roos of Lisp paul graham Draf, January 18, 2002. In 1960, John McCarhy published a remarkable paper in which he did for programming somehing like wha Euclid did for geomery. 1 He showed how, given

More information

Chapter 4 Sequential Instructions

Chapter 4 Sequential Instructions Chaper 4 Sequenial Insrucions The sequenial insrucions of FBs-PLC shown in his chaper are also lised in secion 3.. Please refer o Chaper, "PLC Ladder diagram and he Coding rules of Mnemonic insrucion",

More information

Real Time Integral-Based Structural Health Monitoring

Real Time Integral-Based Structural Health Monitoring Real Time Inegral-Based Srucural Healh Monioring The nd Inernaional Conference on Sensing Technology ICST 7 J. G. Chase, I. Singh-Leve, C. E. Hann, X. Chen Deparmen of Mechanical Engineering, Universiy

More information

A non-stationary uniform tension controlled interpolating 4-point scheme reproducing conics

A non-stationary uniform tension controlled interpolating 4-point scheme reproducing conics A non-saionary uniform ension conrolled inerpolaing 4-poin scheme reproducing conics C. Beccari a, G. Casciola b, L. Romani b, a Deparmen of Pure and Applied Mahemaics, Universiy of Padova, Via G. Belzoni

More information

MB86297A Carmine Timing Analysis of the DDR Interface

MB86297A Carmine Timing Analysis of the DDR Interface Applicaion Noe MB86297A Carmine Timing Analysis of he DDR Inerface Fujisu Microelecronics Europe GmbH Hisory Dae Auhor Version Commen 05.02.2008 Anders Ramdahl 0.01 Firs draf 06.02.2008 Anders Ramdahl

More information

FLOW VISUALIZATION USING MOVING TEXTURES * Nelson Max Lawrence Livermore National Laboratory Livermore, California

FLOW VISUALIZATION USING MOVING TEXTURES * Nelson Max Lawrence Livermore National Laboratory Livermore, California FLOW VISUALIZATION USING MOVING TEXTURES * Nelson Max Lawrence Livermore Naional Laboraor Livermore, California Barr Becker Lawrence Livermore Naional Laboraor Livermore, California SUMMARY We presen a

More information

Effects needed for Realism. Ray Tracing. Ray Tracing: History. Outline. Foundations of Computer Graphics (Fall 2012)

Effects needed for Realism. Ray Tracing. Ray Tracing: History. Outline. Foundations of Computer Graphics (Fall 2012) Foundaions of ompuer Graphics (Fall 2012) S 184, Lecure 16: Ray Tracing hp://ins.eecs.berkeley.edu/~cs184 Effecs needed for Realism (Sof) Shadows Reflecions (Mirrors and Glossy) Transparency (Waer, Glass)

More information

EP2200 Queueing theory and teletraffic systems

EP2200 Queueing theory and teletraffic systems EP2200 Queueing heory and eleraffic sysems Vikoria Fodor Laboraory of Communicaion Neworks School of Elecrical Engineering Lecure 1 If you wan o model neworks Or a comple daa flow A queue's he key o help

More information

Coded Caching with Multiple File Requests

Coded Caching with Multiple File Requests Coded Caching wih Muliple File Requess Yi-Peng Wei Sennur Ulukus Deparmen of Elecrical and Compuer Engineering Universiy of Maryland College Park, MD 20742 ypwei@umd.edu ulukus@umd.edu Absrac We sudy a

More information

AML710 CAD LECTURE 11 SPACE CURVES. Space Curves Intrinsic properties Synthetic curves

AML710 CAD LECTURE 11 SPACE CURVES. Space Curves Intrinsic properties Synthetic curves AML7 CAD LECTURE Space Curves Inrinsic properies Synheic curves A curve which may pass hrough any region of hreedimensional space, as conrased o a plane curve which mus lie on a single plane. Space curves

More information

Lecture 18: Mix net Voting Systems

Lecture 18: Mix net Voting Systems 6.897: Advanced Topics in Crypography Apr 9, 2004 Lecure 18: Mix ne Voing Sysems Scribed by: Yael Tauman Kalai 1 Inroducion In he previous lecure, we defined he noion of an elecronic voing sysem, and specified

More information

Less Pessimistic Worst-Case Delay Analysis for Packet-Switched Networks

Less Pessimistic Worst-Case Delay Analysis for Packet-Switched Networks Less Pessimisic Wors-Case Delay Analysis for Packe-Swiched Neworks Maias Wecksén Cenre for Research on Embedded Sysems P O Box 823 SE-31 18 Halmsad maias.wecksen@hh.se Magnus Jonsson Cenre for Research

More information

Michiel Helder and Marielle C.T.A Geurts. Hoofdkantoor PTT Post / Dutch Postal Services Headquarters

Michiel Helder and Marielle C.T.A Geurts. Hoofdkantoor PTT Post / Dutch Postal Services Headquarters SHORT TERM PREDICTIONS A MONITORING SYSTEM by Michiel Helder and Marielle C.T.A Geurs Hoofdkanoor PTT Pos / Duch Posal Services Headquarers Keywords macro ime series shor erm predicions ARIMA-models faciliy

More information

A Matching Algorithm for Content-Based Image Retrieval

A Matching Algorithm for Content-Based Image Retrieval A Maching Algorihm for Conen-Based Image Rerieval Sue J. Cho Deparmen of Compuer Science Seoul Naional Universiy Seoul, Korea Absrac Conen-based image rerieval sysem rerieves an image from a daabase using

More information

Design Alternatives for a Thin Lens Spatial Integrator Array

Design Alternatives for a Thin Lens Spatial Integrator Array Egyp. J. Solids, Vol. (7), No. (), (004) 75 Design Alernaives for a Thin Lens Spaial Inegraor Array Hala Kamal *, Daniel V azquez and Javier Alda and E. Bernabeu Opics Deparmen. Universiy Compluense of

More information

EECS 487: Interactive Computer Graphics

EECS 487: Interactive Computer Graphics EECS 487: Ineracive Compuer Graphics Lecure 7: B-splines curves Raional Bézier and NURBS Cubic Splines A represenaion of cubic spline consiss of: four conrol poins (why four?) hese are compleely user specified

More information

4 Error Control. 4.1 Issues with Reliable Protocols

4 Error Control. 4.1 Issues with Reliable Protocols 4 Error Conrol Jus abou all communicaion sysems aemp o ensure ha he daa ges o he oher end of he link wihou errors. Since i s impossible o build an error-free physical layer (alhough some shor links can

More information

PART 1 REFERENCE INFORMATION CONTROL DATA 6400 SYSTEMS CENTRAL PROCESSOR MONITOR

PART 1 REFERENCE INFORMATION CONTROL DATA 6400 SYSTEMS CENTRAL PROCESSOR MONITOR . ~ PART 1 c 0 \,).,,.,, REFERENCE NFORMATON CONTROL DATA 6400 SYSTEMS CENTRAL PROCESSOR MONTOR n CONTROL DATA 6400 Compuer Sysems, sysem funcions are normally handled by he Monior locaed in a Peripheral

More information

V103 TRIPLE 10-BIT LVDS TRANSMITTER FOR VIDEO. General Description. Features. Block Diagram

V103 TRIPLE 10-BIT LVDS TRANSMITTER FOR VIDEO. General Description. Features. Block Diagram General Descripion The V103 LVDS display inerface ransmier is primarily designed o suppor pixel daa ransmission beween a video processing engine and a digial video display. The daa rae suppors up o SXGA+

More information

BEST DYNAMICS NAMICS CRM A COMPILATION OF TECH-TIPS TO HELP YOUR BUSINESS SUCCEED WITH DYNAMICS CRM

BEST DYNAMICS NAMICS CRM A COMPILATION OF TECH-TIPS TO HELP YOUR BUSINESS SUCCEED WITH DYNAMICS CRM DYNAMICS CR A Publicaion by elogic s fines Microsof Dynamics CRM Expers { ICS CRM BEST OF 2014 A COMPILATION OF TECH-TIPS TO HELP YOUR BUSINESS SUCCEED WITH DYNAMICS CRM NAMICS CRM { DYNAMICS M INTRODUCTION

More information

Probabilistic Detection and Tracking of Motion Discontinuities

Probabilistic Detection and Tracking of Motion Discontinuities Probabilisic Deecion and Tracking of Moion Disconinuiies Michael J. Black David J. Flee Xerox Palo Alo Research Cener 3333 Coyoe Hill Road Palo Alo, CA 94304 fblack,fleeg@parc.xerox.com hp://www.parc.xerox.com/fblack,fleeg/

More information

Location. Electrical. Loads. 2-wire mains-rated. 0.5 mm² to 1.5 mm² Max. length 300 m (with 1.5 mm² cable). Example: Belden 8471

Location. Electrical. Loads. 2-wire mains-rated. 0.5 mm² to 1.5 mm² Max. length 300 m (with 1.5 mm² cable). Example: Belden 8471 Produc Descripion Insallaion and User Guide Transiser Dimmer (454) The DIN rail mouned 454 is a 4channel ransisor dimmer. I can operae in one of wo modes; leading edge or railing edge. All 4 channels operae

More information

Streamline Pathline Eulerian Lagrangian

Streamline Pathline Eulerian Lagrangian Sreamline Pahline Eulerian Lagrangian Sagnaion Poin Flow V V V = + = + = + o V xi y j a V V xi y j o Pahline and Sreakline Insananeous Sreamlines Pahlines Sreaklines Maerial Derivaive Acceleraion

More information

Outline. EECS Components and Design Techniques for Digital Systems. Lec 06 Using FSMs Review: Typical Controller: state

Outline. EECS Components and Design Techniques for Digital Systems. Lec 06 Using FSMs Review: Typical Controller: state Ouline EECS 5 - Componens and Design Techniques for Digial Sysems Lec 6 Using FSMs 9-3-7 Review FSMs Mapping o FPGAs Typical uses of FSMs Synchronous Seq. Circuis safe composiion Timing FSMs in verilog

More information

Experiments in Generalizing Geometry Theorems Stephen B. Gray

Experiments in Generalizing Geometry Theorems Stephen B. Gray Experimens in Generalizing Geomery Theorems Sephen B. Gray. INTRODUCTION: THE PDN THEOREM Well-known advances in geomery have been made wih experimenal, or compueraided echniques. The irs was he proo o

More information

Voltair Version 2.5 Release Notes (January, 2018)

Voltair Version 2.5 Release Notes (January, 2018) Volair Version 2.5 Release Noes (January, 2018) Inroducion 25-Seven s new Firmware Updae 2.5 for he Volair processor is par of our coninuing effors o improve Volair wih new feaures and capabiliies. For

More information

MIC2569. Features. General Description. Applications. Typical Application. CableCARD Power Switch

MIC2569. Features. General Description. Applications. Typical Application. CableCARD Power Switch CableCARD Power Swich General Descripion is designed o supply power o OpenCable sysems and CableCARD hoss. These CableCARDs are also known as Poin of Disribuion (POD) cards. suppors boh Single and Muliple

More information

Improving the Efficiency of Dynamic Service Provisioning in Transport Networks with Scheduled Services

Improving the Efficiency of Dynamic Service Provisioning in Transport Networks with Scheduled Services Improving he Efficiency of Dynamic Service Provisioning in Transpor Neworks wih Scheduled Services Ralf Hülsermann, Monika Jäger and Andreas Gladisch Technologiezenrum, T-Sysems, Goslarer Ufer 35, D-1585

More information

A Fast Stereo-Based Multi-Person Tracking using an Approximated Likelihood Map for Overlapping Silhouette Templates

A Fast Stereo-Based Multi-Person Tracking using an Approximated Likelihood Map for Overlapping Silhouette Templates A Fas Sereo-Based Muli-Person Tracking using an Approximaed Likelihood Map for Overlapping Silhouee Templaes Junji Saake Jun Miura Deparmen of Compuer Science and Engineering Toyohashi Universiy of Technology

More information

FACIAL ACTION TRACKING USING PARTICLE FILTERS AND ACTIVE APPEARANCE MODELS. Soumya Hamlaoui & Franck Davoine

FACIAL ACTION TRACKING USING PARTICLE FILTERS AND ACTIVE APPEARANCE MODELS. Soumya Hamlaoui & Franck Davoine FACIAL ACTION TRACKING USING PARTICLE FILTERS AND ACTIVE APPEARANCE MODELS Soumya Hamlaoui & Franck Davoine HEUDIASYC Mixed Research Uni, CNRS / Compiègne Universiy of Technology BP 20529, 60205 Compiègne

More information

Outline Introduction. Digital Applications (Cont d) Classification of Control Systems. Discrete-time Control Applications

Outline Introduction. Digital Applications (Cont d) Classification of Control Systems. Discrete-time Control Applications Ouline Inroducion Classiicaion o Conrol Sysems Classiicaion o Conrol Sysems Analog Conrollers Op-amp circuis PID Implemenaion Comparison Signals in Conrol Engineering Elemens o Conrol Compuer I/O ineraces

More information

A Principled Approach to. MILP Modeling. Columbia University, August Carnegie Mellon University. Workshop on MIP. John Hooker.

A Principled Approach to. MILP Modeling. Columbia University, August Carnegie Mellon University. Workshop on MIP. John Hooker. Slide A Principled Approach o MILP Modeling John Hooer Carnegie Mellon Universiy Worshop on MIP Columbia Universiy, Augus 008 Proposal MILP modeling is an ar, bu i need no be unprincipled. Slide Proposal

More information

Data Structures and Algorithms. The material for this lecture is drawn, in part, from The Practice of Programming (Kernighan & Pike) Chapter 2

Data Structures and Algorithms. The material for this lecture is drawn, in part, from The Practice of Programming (Kernighan & Pike) Chapter 2 Daa Srucures and Algorihms The maerial for his lecure is drawn, in par, from The Pracice of Programming (Kernighan & Pike) Chaper 2 1 Moivaing Quoaion Every program depends on algorihms and daa srucures,

More information

CS 152 Computer Architecture and Engineering. Lecture 7 - Memory Hierarchy-II

CS 152 Computer Architecture and Engineering. Lecture 7 - Memory Hierarchy-II CS 152 Compuer Archiecure and Engineering Lecure 7 - Memory Hierarchy-II Krse Asanovic Elecrical Engineering and Compuer Sciences Universiy of California a Berkeley hp://www.eecs.berkeley.edu/~krse hp://ins.eecs.berkeley.edu/~cs152

More information

7.2 Puiseux Expansions

7.2 Puiseux Expansions 7. Puiseux Expansions Given an algebraic funcion on an algebraic curve, we wish o compue is principle pars by locaing is poles and compuing series expansions here. Since he powers of y form a Cx basis

More information

TUTORING TEXTS IN MATHCAD

TUTORING TEXTS IN MATHCAD TUTORING TEXTS IN MATHCAD MIROSLAV DOLOZÍILEK and ANNA RYNDOVÁ Faculy of Mechanical Engineering, Brno Universiy of Technology Technická, 616 69 Brno, Czech Republic E-ail: irdo@fyzika.fe.vubr.cz Absrac

More information

Low-Cost WLAN based. Dr. Christian Hoene. Computer Science Department, University of Tübingen, Germany

Low-Cost WLAN based. Dr. Christian Hoene. Computer Science Department, University of Tübingen, Germany Low-Cos WLAN based Time-of-fligh fligh Trilaeraion Precision Indoor Personnel Locaion and Tracking for Emergency Responders Third Annual Technology Workshop, Augus 5, 2008 Worceser Polyechnic Insiue, Worceser,

More information

(Structural Time Series Models for Describing Trend in All India Sunflower Yield Using SAS

(Structural Time Series Models for Describing Trend in All India Sunflower Yield Using SAS (Srucural Time Series Models for Describing Trend in All India Sunflower Yield Using SAS Himadri Ghosh, Prajneshu and Savia Wadhwa I.A.S.R.I., Library Avenue, New Delhi-110 01 him_adri@iasri.res.in, prajnesh@iasri.res.in,

More information

A Hardware Implementation of the Compact Genetic Algorithm

A Hardware Implementation of the Compact Genetic Algorithm A Hardware Implemenaion of he Compac Geneic Algorihm Chachawi Apornewan Deparmen of Compuer Engineering Faculy of Engineering, Chulalongkorn Universiy Bangkok 0330, Thailand 437043@chula.ac.h Prabhas Chongsivaana

More information

A Fast Non-Uniform Knots Placement Method for B-Spline Fitting

A Fast Non-Uniform Knots Placement Method for B-Spline Fitting 2015 IEEE Inernaional Conference on Advanced Inelligen Mecharonics (AIM) July 7-11, 2015. Busan, Korea A Fas Non-Uniform Knos Placemen Mehod for B-Spline Fiing T. Tjahjowidodo, VT. Dung, and ML. Han Absrac

More information

Nonparametric CUSUM Charts for Process Variability

Nonparametric CUSUM Charts for Process Variability Journal of Academia and Indusrial Research (JAIR) Volume 3, Issue June 4 53 REEARCH ARTICLE IN: 78-53 Nonparameric CUUM Chars for Process Variabiliy D.M. Zombade and V.B. Ghue * Dep. of aisics, Walchand

More information

Computer aided design and pattering of tensioned fabric structures

Computer aided design and pattering of tensioned fabric structures Compuer aided design and paering of ensioned fabric srucures Bharah Gowda Designer/Engineer, Advanced Srucures Inc. 4094 Glencoe Ave., Marina del Rey, CA 90292, USA. Telphone: 310-310 1984 Fax: 310-310

More information

An efficient approach to improve throughput for TCP vegas in ad hoc network

An efficient approach to improve throughput for TCP vegas in ad hoc network Inernaional Research Journal of Engineering and Technology (IRJET) e-issn: 395-0056 Volume: 0 Issue: 03 June-05 www.irje.ne p-issn: 395-007 An efficien approach o improve hroughpu for TCP vegas in ad hoc

More information

Optimal Crane Scheduling

Optimal Crane Scheduling Opimal Crane Scheduling Samid Hoda, John Hooker Laife Genc Kaya, Ben Peerson Carnegie Mellon Universiy Iiro Harjunkoski ABB Corporae Research EWO - 13 November 2007 1/16 Problem Track-mouned cranes move

More information

Principles of MRI EE225E / BIO265. Lecture 10. Instructor: Miki Lustig UC Berkeley, EECS. M. Lustig, EECS UC Berkeley

Principles of MRI EE225E / BIO265. Lecture 10. Instructor: Miki Lustig UC Berkeley, EECS. M. Lustig, EECS UC Berkeley Principles of MRI Lecure 0 EE225E / BIO265 Insrucor: Miki Lusig UC Berkeley, EECS Bloch Eq. For Recepion No B() : 2 4 Ṁ x Ṁ y Ṁ z 3 5 = 2 6 4 T 2 ~ G ~r 0 ~G ~r T 2 0 0 0 T 3 2 7 5 4 M x M y M z 3 5 +

More information

MORPHOLOGICAL SEGMENTATION OF IMAGE SEQUENCES

MORPHOLOGICAL SEGMENTATION OF IMAGE SEQUENCES MORPHOLOGICAL SEGMENTATION OF IMAGE SEQUENCES B. MARCOTEGUI and F. MEYER Ecole des Mines de Paris, Cenre de Morphologie Mahémaique, 35, rue Sain-Honoré, F 77305 Fonainebleau Cedex, France Absrac. In image

More information

Evaluation and Improvement of Region-based Motion Segmentation

Evaluation and Improvement of Region-based Motion Segmentation Evaluaion and Improvemen of Region-based Moion Segmenaion Mark Ross Universiy Koblenz-Landau, Insiue of Compuaional Visualisics, Universiässraße 1, 56070 Koblenz, Germany Email: ross@uni-koblenz.de Absrac

More information

An Improved Square-Root Nyquist Shaping Filter

An Improved Square-Root Nyquist Shaping Filter An Improved Square-Roo Nyquis Shaping Filer fred harris San Diego Sae Universiy fred.harris@sdsu.edu Sridhar Seshagiri San Diego Sae Universiy Seshigar.@engineering.sdsu.edu Chris Dick Xilinx Corp. chris.dick@xilinx.com

More information

Spline Curves. Color Interpolation. Normal Interpolation. Last Time? Today. glshademodel (GL_SMOOTH); Adjacency Data Structures. Mesh Simplification

Spline Curves. Color Interpolation. Normal Interpolation. Last Time? Today. glshademodel (GL_SMOOTH); Adjacency Data Structures. Mesh Simplification Las Time? Adjacency Daa Srucures Spline Curves Geomeric & opologic informaion Dynamic allocaion Efficiency of access Mesh Simplificaion edge collapse/verex spli geomorphs progressive ransmission view-dependen

More information

Projection & Interaction

Projection & Interaction Projecion & Ineracion Algebra of projecion Canonical viewing volume rackball inerface ransform Hierarchies Preview of Assignmen #2 Lecure 8 Comp 236 Spring 25 Projecions Our lives are grealy simplified

More information

Dynamic Route Planning and Obstacle Avoidance Model for Unmanned Aerial Vehicles

Dynamic Route Planning and Obstacle Avoidance Model for Unmanned Aerial Vehicles Volume 116 No. 24 2017, 315-329 ISSN: 1311-8080 (prined version); ISSN: 1314-3395 (on-line version) url: hp://www.ijpam.eu ijpam.eu Dynamic Roue Planning and Obsacle Avoidance Model for Unmanned Aerial

More information

In this paper we discuss the automatic construction of. are Delaunay triangulations whose smallest angles are bounded and, in

In this paper we discuss the automatic construction of. are Delaunay triangulations whose smallest angles are bounded and, in uomaic consrucion of qualiy nonobuse boundary Delaunay riangulaions Nancy Hischfeld and ara-ecilia Rivara Deparmen of ompuer Science, Universiy of hile, casilla 2777, Saniago, HILE e-mail: nancy@dcc.uchile.cl,

More information

Incorporating Level Set Methods in Geographical Information Systems (GIS) for Land-Surface Process Modeling

Incorporating Level Set Methods in Geographical Information Systems (GIS) for Land-Surface Process Modeling Incorporaing Level Se Mehods in Geographical Informaion Sysems (GIS) for Land-Surface Process Modeling D. Pullar Geography Planning and Archiecure, The Universiy of Queensland, Brisbane QLD 4072, Ausralia

More information

In Proceedings of CVPR '96. Structure and Motion of Curved 3D Objects from. using these methods [12].

In Proceedings of CVPR '96. Structure and Motion of Curved 3D Objects from. using these methods [12]. In Proceedings of CVPR '96 Srucure and Moion of Curved 3D Objecs from Monocular Silhouees B Vijayakumar David J Kriegman Dep of Elecrical Engineering Yale Universiy New Haven, CT 652-8267 Jean Ponce Compuer

More information

Computer representations of piecewise

Computer representations of piecewise Edior: Gabriel Taubin Inroducion o Geomeric Processing hrough Opimizaion Gabriel Taubin Brown Universiy Compuer represenaions o piecewise smooh suraces have become vial echnologies in areas ranging rom

More information

Exercise 3: Bluetooth BR/EDR

Exercise 3: Bluetooth BR/EDR Wireless Communicaions, M. Rupf. Exercise 3: Blueooh BR/EDR Problem 1: Blueooh Daa Raes. Consider he ACL packe 3-DH5 wih a maximum user payload of 1021 byes. a) Deermine he maximum achievable daa rae in

More information

Automatic Calculation of Coverage Profiles for Coverage-based Testing

Automatic Calculation of Coverage Profiles for Coverage-based Testing Auomaic Calculaion of Coverage Profiles for Coverage-based Tesing Raimund Kirner 1 and Waler Haas 1 Vienna Universiy of Technology, Insiue of Compuer Engineering, Vienna, Ausria, raimund@vmars.uwien.ac.a

More information

USBFC (USB Function Controller)

USBFC (USB Function Controller) USBFC () EIFUFAL501 User s Manual Doc #: 88-02-E01 Revision: 2.0 Dae: 03/24/98 (USBFC) 1. Highlighs... 4 1.1 Feaures... 4 1.2 Overview... 4 1.3 USBFC Block Diagram... 5 1.4 USBFC Typical Sysem Block Diagram...

More information

Hermite Curves. Jim Armstrong Singularity November 2005

Hermite Curves. Jim Armstrong Singularity November 2005 TechNoe TN-5- Herie Curves Ji Arsrong Singulariy Noveer 5 This is he second in a series of TechNoes on he sujec of applied curve aheaics in Adoe Flash TM. Each TechNoe provides a aheaical foundaion for

More information

Hybrid Equations (HyEQ) Toolbox v2.02 A Toolbox for Simulating Hybrid Systems in MATLAB/Simulink R

Hybrid Equations (HyEQ) Toolbox v2.02 A Toolbox for Simulating Hybrid Systems in MATLAB/Simulink R Hybrid Equaions (HyEQ) Toolbo v. A Toolbo for Simulaing Hybrid Sysems in MATLAB/Simulink R Ricardo G. Sanfelice Universiy of California Sana Cruz, CA 9564 USA David A. Copp Universiy of California Sana

More information

Differential Geometry of Surfaces with Mathcad: A Virtual Learning Approach

Differential Geometry of Surfaces with Mathcad: A Virtual Learning Approach The 4 h Inernaional Conference on Virual Learning Gheorghe Asachi Technical Universiy of Iaşi, Oc 30-Nov, 009 Differenial Geomery of Surfaces wih Mahca: A Virual Learning Approach Nicolae Dăneţ Technical

More information

Test - Accredited Configuration Engineer (ACE) Exam - PAN-OS 6.0 Version

Test - Accredited Configuration Engineer (ACE) Exam - PAN-OS 6.0 Version Tes - Accredied Configuraion Engineer (ACE) Exam - PAN-OS 6.0 Version ACE Exam Quesion 1 of 50. Which of he following saemens is NOT abou Palo Alo Neworks firewalls? Sysem defauls may be resored by performing

More information