Photovoltaic Panel Modelling Using a Stochastic Approach in MATLAB &Simulink

Size: px
Start display at page:

Download "Photovoltaic Panel Modelling Using a Stochastic Approach in MATLAB &Simulink"

Transcription

1 hotovolti nel Modelling Using Stohsti Approh in MATLAB &Simulink KAREL ZALATILEK, JAN LEUCHTER eprtment of Eletril Engineering University of efene Kouniov 65, 61 City of Brno CZECH REUBLIC Astrt: - The topi of this pper is development of mthemtil model of rel photovolti pnel, sed upon long term mesurements, using stohsti pproh The input is the dt of typil power-voltge hrteristi mesured on the String inverter The output is n integrted prmetri model whih n ontrol the pnel s operting point with the use of the solr irrdition The rtile expnds the originl ide of the impliit pproximtion pulished in [1] with the possiility of the prmetri ontrol The mthemtil model developed in MATLAB is ompleted in the form of funtionl lok model in Simulink s hierrhil model The dvntge is n esy hnge of the pnel y rewriting severl onstnts nd lso inluding the mesures of temperture, if ville The enefit of this pproh is the inlusion of ll the influenes on the pnel, suh s losses, ging, rndom errors, et Key-Words: - impliit pproximtion, MATLAB &Simulink, photovolti pnel modelling, stohsti pproh 1 Introdution The previous pper [1] ontins the originl method of the pproximtion of long term mesurements of rel photovolti pnel p/v hrteristi, sed on n impliit irle eqution The eqution oeffiients long with the pproximtion intervls of power nd voltge re the output of the lgorithm The impliit irle eqution in the quoted prmeter is derived with the use of the symoli mthemtis in the MATLAB environment The disussed pproximtion lgorithm is fully usele; however, it does not inlude these importnt onditions nd possiilities: rmetri ontrol of the operting point with the solr irrdition Numeril lgorithm for the lultion of power nd voltge Blok form of the model for further experiments The essene of this rtile is the innovtion of the originl pproximtion method with the three mentioned hrteristis of the model The min output, mong other, is fully funtionl prmetri model of rel pnel in the Simulink environment The originl sript for the desription of its essentil hrteristis ws developed in MATLAB whih is well suited for oth input of the p/v hrteristi mesurements nd other hrteristis desried elow Impliit pproximtion of p/v hrteristis This hpter riefly introdues the min priniples nd outputs of the pproximtion lgorithm desried in [1] The lgorithm inputs re: Long term mesurements of the pnel s p/v hrteristi Three points on the hrteristi hosen either mnully or utomtilly The typil outputs re: An impliit irle eqution pproximting the given ourse A rnge of the pproximtion intervl of power nd voltge The Figure 1 shows typil result of long term p/v hrteristi mesurement nd the ourse of the pproximtion irle It is stohsti pproh nd the ISBN:

2 pnel works lose to the MT mode (Mximum ower oint Trking) [] Every point of the hrteristi is influened y the solr irrdition t given time nd represents n operting point t tht time ower (W) Mesured /V hrteristi nd pproximting irle r,1, whih is more suitle for the modelling purposes The disussed model n work with oth solute nd reltive vlues of irrdition ue to the impliit hrter of the pproximtion irle ording to the Figure, the following proedure ws hosen: Approximtion of the ourse p=f( r ) Clultion of speifi power for speified irrdition r Clultion of voltge V from the known power ording to the impliit eqution (qudrti eqution solution) The lgorithm is lerly desried y the lok sheme shown in Figure Voltge (V) Fig1 Long-term mesured p/v hrteristis nd its pproximtion [1] The Figure shows typil output of the pproximtion lgorithm, whih is n impliit eqution of the pproximtion irle nd rnge of the power nd voltge intervls The numer of deiml ples is redued for the in order to sve spe K1, K, K3, K4, K5 ower lultion on the sis Voltge V lultion on the sis Operting point drwing in p/v Input onstnts pproximtion of p=f( r ) Qudrti eqution solution Fig3 Blok digrm of operting point ontrol definition Fig Typil pproximting lgorithm output in MATLAB 3 rmetri operting point ontrol The min ojetive of our originl method is to omplete the prmetri ontrol of the pproximtion urve in the Figure 1 The min prmeter in prtie is the irrdition of the pnel (Wm - ), or the reltive irrdition For the possiility of ontrol of the operting point with the irrdition, defult liner dependene etween power nd reltive irrdition p=f( r ) ws set ording to the formul: p = k + r q ( W ), (1) where k nd q re the slope of the pproximtion line nd its shift The onstnts k nd q n e esily lulted from the input onstnts in Figure 3: mx min k = ( W), q = min (W) () r mx r min If the lulted power is known, then it is neessry to lulte the power on the horizontl xis of the grph ISBN:

3 in Figure 1 To do tht, the derived impliit eqution nd its oeffiients hve to e used Sustituting the known power to the impliit eqution, the eqution is simplified to this generl form: v + v + = (3) For the lultion of voltge ording to (3) it is neessry to define the onstnts, nd By ompring with the originl impliit eqution nd the expression (3) they n e defined s follows: = K5; = K 4; = K3 + K + K1 (4) The next step is the solution to the qudrti eqution (3) for the known vlues of the onstnts,, nd This is solved with well-known formul: ± V1, =, = 4 (5) The numeril lultion shows tht only the seond root for whih pplies tht V > is physilly suitle If the numeril vlues of power nd voltge V re known for the defined reltive irrdition r, the speified operting point of the p/v hrteristi n e drwn 4 rtil exmple Let us onsider rel photovolti pnel with nominl power n =1 W tht opertes in our deprtment nd for whih the mesured dt in Figure 1 re vlid The oeffiients of n impliit pproximtion irle for this pnel were lulted ording to Figure It is true tht: mx r mx = 1158 W, = 1, = r min min = W Let us hve speified reltive irrdition r =45 Aording to (), the slope nd the shift of the pproximtion line p/ r n e lulted: 1158 k = = 8158 W, q = W 1 Aording to (1) the vlue of power is =56711W Aording to (4) nd (5), the vlues of the uxiliry onstnts nd the disriminnt re lulted The resulting voltge ording to the first prt of the eqution (5) is: V = 1541V The Figure 4 shows the lulted operting point long with its oordintes With the speifition of reltive solr irrdition; the whole p/v urve is drwn It should e emphsized tht users n lso use other rnge of the reltive irrdition vetor ording to their needs ower (W) Simulted /V hrteristi ower (W): Voltge (V): 1541 r (-): Voltge (V) Fig4 Operting point lultion for required vlues In tht se the prmeters of the pproximtion line will hnge ordingly (1) nd () The limits of the vetors of power nd voltge re inluded in the Figure The Figure 5 shows the experimentl lortory for the long term mesurements nd dt proessing from rel photovolti pnel, see lso the Figure 1 The red devie in the upper left orner is String inverter SUNNY BOY 11, with whih the dt were olleted The mesured pnel is professionl photovolti system Shüo ME S 5 Serie Fig5 Workple for photovolti pnel mesurement nd simultion ISBN:

4 5 Soure ode in MATLAB The min prts of the lultion were relized t first in MATLAB s sript The Figure 6 shows seleted key prts of the soure ode with desription Some of the formtting ommnds were omitted due to the lk of spe The soure ode is supposed to e ler nd understndle nd is in the full ompline with the presented theoretil desription One of the lgorithm outputs is the ourse of the p/v hrteristi whih fully orresponds to the Figure 1, see the Figure 7 It should e noted tht the lultion of the key prmeters is solved numerilly, prt from the proedure desried in [1], where the symoli mthemtis of MATLAB environment ws used for the derivtion of the oeffiients of the impliit irle eqution Fig7 Simulted p/v hrteristis s typil lgorithm output 6 Blok model in Simulink The min ojetive ws to set up funtionl model of pnel in Simulink The Figure 8 shows the resulting model where the tul pnel is presented in the form of susystem The ontrolling reltive irrdition is presented s onstnt (mnul input) or s hrmoni genertor Fig6 MATLAB soure ode of lgorithm key prt The numeril pproh ws hosen deliertely for the purposes of the implementtion in the Simulink environment, see elow Fig8 Resulting lok model in Simulink ISBN:

5 The pnel n e ontrolled in ny other wy, e g the dt from disk or mesuring rd, or y rndom genertor The lulted prmeters orrespond to the results in the hpter 4 Rel photovolti pnel model sed on long-term mesurement Sine Irrdition ( -1) Step 1 onstnts definition Swith [1] [] [hi1] [hi] [hi] hi1 45 [hi] hi [K4] [] 5671 Output power Constnts Voltge1 [1] [] [hi1] [hi] Step power lultion [] ower [] [K3] [K] [K1] Step 4 disriminnt lultion [K4] 154 Output voltge1 [] ower1 [hi] 45 hi mx min himx himin ower nd hi limits mx min himx himin hi ower =^-4 isriminnt [] Input irrdition [] Voltge [] ower Constnts K1 K K3 K4 K5 Impliit oeffiients K3 K K1 Clultion of onstnt V Voltge [K1] [K] [K3] [K4] Step 3 lultion of "" [] 1 Step 5 voltge lultion Output voltge =f(v) Fig9 etiled internl struture of the Simulink lok model The Figure 9 shows the model of the whole pnel in more detil It lso presents the proedurl steps in ompline with the theoretil proedure mentioned ove in Figure 3 The lultions of the power, the disriminnt nd the resulting voltge orrespond to the equtions (1) to (5) The numeril outputs were kept to hek the ove mentioned numeril exmple The min output of the lok model in the Figure 9 is the grph of the p/v hrteristi By setting the mnul swith to the hrmoni ourse of the reltive irrdition the whole simulted hrteristi p/v is otined ording to Figure 7 The ourse of the reltive irrdition is then defined s: r = 5sin(πFt), F = 1Hz The vlue of the mximum time in the Simulink ws set to T mx =1s Considering the nture of the tsk disrete type solver ws set, nd the mximum step to the vlue 1/5 The inner struture of the susystems in the Figure 9 orresponds to the ove mentioned proedure After liking on the susystem for setting the onstnts it is possile to hnge the type of pnel nd the limits of the reltive irrdition t ny time A lrge numer of works on this topi hs een pulished reently, eg [3], [4] 7 Conlusion This rtile presents the originl lgorithm of development of rel photovolti pnel model The model is sed on the long time mesurements of the p/v hrteristi The presented proedure follows the works pulished in [1] tht ontin the proedure of lultion of the impliit irle eqution oeffiients tht pproximte the mesured dt In this pper, the disussed model ws expnded with the option of prmetril ontrol with reltive solr irrdition nd finlized in the lgorithmi form in the MATLAB environment nd the Simulink lok model The experimentl nd simultion works fully justify the legitimy of the model Aknowledgements MATLAB nd Simulink re registered trdemrks of The MthWorks, In Referenes: [1] K Zpltilek, J Leuhter, Impliit Approximtion of hotovolti nel Chrteristis Using Stohsti Approh, Advnes in Eletril nd Computer Engineering, 1, vol 1, no 4, pp [] J Leuhter, V Reruh, A F Zo, Mthemtil modeling of photovolti systems, in ro 14th ower Eletronis nd Motion Control Conferene (EE-EMC 1), Ohrid (Medoni), 1, pp 4-47 [3] R M d Silv, J L M Fernndes, Hyrid hotovolti/therml (V/T) Solr Systems Simultion with Simulink &MATLAB, Solr Energy, 1, Vol 84, Issue 1, pp [4] S Llouni, Rekiou, Modeling nd Simultion of hotovolti System Using Fuzzy Logi Controller, in ro nd Interntionl Conferene on evelopments in Systems Engineering, Au hi, Ar Emirtes, 9, pp 3-8 ISBN:

Duality in linear interval equations

Duality in linear interval equations Aville online t http://ijim.sriu..ir Int. J. Industril Mthemtis Vol. 1, No. 1 (2009) 41-45 Dulity in liner intervl equtions M. Movhedin, S. Slhshour, S. Hji Ghsemi, S. Khezerloo, M. Khezerloo, S. M. Khorsny

More information

CS 241 Week 4 Tutorial Solutions

CS 241 Week 4 Tutorial Solutions CS 4 Week 4 Tutoril Solutions Writing n Assemler, Prt & Regulr Lnguges Prt Winter 8 Assemling instrutions utomtilly. slt $d, $s, $t. Solution: $d, $s, nd $t ll fit in -it signed integers sine they re 5-it

More information

Error Numbers of the Standard Function Block

Error Numbers of the Standard Function Block A.2.2 Numers of the Stndrd Funtion Blok evlution The result of the logi opertion RLO is set if n error ours while the stndrd funtion lok is eing proessed. This llows you to rnh to your own error evlution

More information

[Prakash* et al., 5(8): August, 2016] ISSN: IC Value: 3.00 Impact Factor: 4.116

[Prakash* et al., 5(8): August, 2016] ISSN: IC Value: 3.00 Impact Factor: 4.116 [Prksh* et l 58: ugust 6] ISSN: 77-9655 I Vlue: Impt Ftor: 6 IJESRT INTERNTIONL JOURNL OF ENGINEERING SIENES & RESERH TEHNOLOGY SOME PROPERTIES ND THEOREM ON FUZZY SU-TRIDENT DISTNE Prveen Prksh* M Geeth

More information

Smart Output Field Installation for M-Series and L-Series Converter

Smart Output Field Installation for M-Series and L-Series Converter Smrt Output Field Instlltion for M-Series nd L-Series Converter Instlltion Proedure -- See setion 5.0, Instlltion Proedure 1. Open the Housing nd Prepre for Instlltion 2. Plug the Rion Cle into the Min

More information

Additional Measurement Algorithms in the Overhauser Magnetometer POS-1

Additional Measurement Algorithms in the Overhauser Magnetometer POS-1 Additionl Mesurement Algorithms in the Overhuser Mgnetometer POS-1 O.V. Denisov, A.Y. Denisov, V.A. Spunov (QM Lortory of Url Stte Tehnil University, Mir 19, Ekterinurg, 620002, Russi) J.L. Rsson (Royl

More information

CMPUT101 Introduction to Computing - Summer 2002

CMPUT101 Introduction to Computing - Summer 2002 CMPUT Introdution to Computing - Summer 22 %XLOGLQJ&RPSXWHU&LUFXLWV Chpter 4.4 3XUSRVH We hve looked t so fr how to uild logi gtes from trnsistors. Next we will look t how to uild iruits from logi gtes,

More information

A METHOD FOR CHARACTERIZATION OF THREE-PHASE UNBALANCED DIPS FROM RECORDED VOLTAGE WAVESHAPES

A METHOD FOR CHARACTERIZATION OF THREE-PHASE UNBALANCED DIPS FROM RECORDED VOLTAGE WAVESHAPES A METHOD FOR CHARACTERIZATION OF THREE-PHASE UNBALANCED DIPS FROM RECORDED OLTAGE WAESHAPES M.H.J. Bollen, L.D. Zhng Dept. Eletri Power Engineering Chlmers University of Tehnology, Gothenurg, Sweden Astrt:

More information

Fault tree conversion to binary decision diagrams

Fault tree conversion to binary decision diagrams Loughorough University Institutionl Repository Fult tree onversion to inry deision digrms This item ws sumitted to Loughorough University's Institutionl Repository y the/n uthor. Cittion: ANDREWS, J.D.

More information

Parallelization Optimization of System-Level Specification

Parallelization Optimization of System-Level Specification Prlleliztion Optimiztion of System-Level Speifition Luki i niel. Gjski enter for Emedded omputer Systems University of liforni Irvine, 92697, US {li, gjski} @es.ui.edu strt This pper introdues the prlleliztion

More information

McAfee Web Gateway

McAfee Web Gateway Relese Notes Revision C MAfee We Gtewy 7.6.2.11 Contents Aout this relese Enhnement Resolved issues Instlltion instrutions Known issues Additionl informtion Find produt doumenttion Aout this relese This

More information

Distributed Systems Principles and Paradigms

Distributed Systems Principles and Paradigms Distriuted Systems Priniples nd Prdigms Christoph Dorn Distriuted Systems Group, Vienn University of Tehnology.dorn@infosys.tuwien..t http://www.infosys.tuwien..t/stff/dorn Slides dpted from Mrten vn Steen,

More information

Distance Computation between Non-convex Polyhedra at Short Range Based on Discrete Voronoi Regions

Distance Computation between Non-convex Polyhedra at Short Range Based on Discrete Voronoi Regions Distne Computtion etween Non-onvex Polyhedr t Short Rnge Bsed on Disrete Voronoi Regions Ktsuki Kwhi nd Hiroms Suzuki Deprtment of Preision Mhinery Engineering, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku,

More information

Paradigm 5. Data Structure. Suffix trees. What is a suffix tree? Suffix tree. Simple applications. Simple applications. Algorithms

Paradigm 5. Data Structure. Suffix trees. What is a suffix tree? Suffix tree. Simple applications. Simple applications. Algorithms Prdigm. Dt Struture Known exmples: link tble, hep, Our leture: suffix tree Will involve mortize method tht will be stressed shortly in this ourse Suffix trees Wht is suffix tree? Simple pplitions History

More information

Width and Bounding Box of Imprecise Points

Width and Bounding Box of Imprecise Points Width nd Bounding Box of Impreise Points Vhideh Keikh Mrten Löffler Ali Mohdes Zhed Rhmti Astrt In this pper we study the following prolem: we re given set L = {l 1,..., l n } of prllel line segments,

More information

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems Distriuted Systems Priniples nd Prdigms Mrten vn Steen VU Amsterdm, Dept. Computer Siene steen@s.vu.nl Chpter 11: Distriuted File Systems Version: Deemer 10, 2012 2 / 14 Distriuted File Systems Distriuted

More information

UTMC APPLICATION NOTE UT1553B BCRT TO INTERFACE PSEUDO-DUAL-PORT RAM ARCHITECTURE INTRODUCTION ARBITRATION DETAILS DESIGN SELECTIONS

UTMC APPLICATION NOTE UT1553B BCRT TO INTERFACE PSEUDO-DUAL-PORT RAM ARCHITECTURE INTRODUCTION ARBITRATION DETAILS DESIGN SELECTIONS UTMC APPLICATION NOTE UT1553B BCRT TO 80186 INTERFACE INTRODUCTION The UTMC UT1553B BCRT is monolithi CMOS integrte iruit tht provies omprehensive Bus Controller n Remote Terminl funtions for MIL-STD-

More information

Calculus Differentiation

Calculus Differentiation //007 Clulus Differentition Jeffrey Seguritn person in rowot miles from the nerest point on strit shoreline wishes to reh house 6 miles frther down the shore. The person n row t rte of mi/hr nd wlk t rte

More information

SMALL SIZE EDGE-FED SIERPINSKI CARPET MICROSTRIP PATCH ANTENNAS

SMALL SIZE EDGE-FED SIERPINSKI CARPET MICROSTRIP PATCH ANTENNAS Progress In Eletromgnetis Reserh C, Vol. 3, 195 22, 28 SMALL SIZE EDGE-FED SIERPINSKI CARPET MICROSTRIP PATCH ANTENNAS W.-L. Chen nd G.-M. Wng Rdr Engineering Deprtment Missile Institute of Air Fore Engineering

More information

Introduction to Algebra

Introduction to Algebra INTRODUCTORY ALGEBRA Mini-Leture 1.1 Introdution to Alger Evlute lgeri expressions y sustitution. Trnslte phrses to lgeri expressions. 1. Evlute the expressions when =, =, nd = 6. ) d) 5 10. Trnslte eh

More information

GENG2140 Modelling and Computer Analysis for Engineers

GENG2140 Modelling and Computer Analysis for Engineers GENG4 Moelling n Computer Anlysis or Engineers Letures 9 & : Gussin qurture Crete y Grn Romn Joles, PhD Shool o Mehnil Engineering, UWA GENG4 Content Deinition o Gussin qurture Computtion o weights n points

More information

Final Exam Review F 06 M 236 Be sure to look over all of your tests, as well as over the activities you did in the activity book

Final Exam Review F 06 M 236 Be sure to look over all of your tests, as well as over the activities you did in the activity book inl xm Review 06 M 236 e sure to loo over ll of your tests, s well s over the tivities you did in the tivity oo 1 1. ind the mesures of the numered ngles nd justify your wor. Line j is prllel to line.

More information

Lecture 12 : Topological Spaces

Lecture 12 : Topological Spaces Leture 12 : Topologil Spes 1 Topologil Spes Topology generlizes notion of distne nd loseness et. Definition 1.1. A topology on set X is olletion T of susets of X hving the following properties. 1. nd X

More information

COMPUTATION AND VISUALIZATION OF REACHABLE DISTRIBUTION NETWORK SUBSTATION VOLTAGE

COMPUTATION AND VISUALIZATION OF REACHABLE DISTRIBUTION NETWORK SUBSTATION VOLTAGE 24 th Interntionl Conferene on Eletriity Distriution Glsgow, 12-15 June 2017 Pper 0615 COMPUTATION AND VISUALIZATION OF REACHABLE DISTRIBUTION NETWORK SUBSTATION VOLTAGE Mihel SANKUR Dniel ARNOLD Lun SCHECTOR

More information

Outline. Motivation Background ARCH. Experiment Additional usages for Input-Depth. Regular Expression Matching DPI over Compressed HTTP

Outline. Motivation Background ARCH. Experiment Additional usages for Input-Depth. Regular Expression Matching DPI over Compressed HTTP ARCH This work ws supported y: The Europen Reserh Counil, The Isreli Centers of Reserh Exellene, The Neptune Consortium, nd Ntionl Siene Foundtion wrd CNS-119748 Outline Motivtion Bkground Regulr Expression

More information

McAfee Network Security Platform

McAfee Network Security Platform Pssive Fil-Open Kit Quik Strt Guide Revision D MAfee Network Seurity Pltform MAfee Network Seurity Pltform IPS Sensors, when deployed in-line, route ll inoming trffi through designted port pir. However,

More information

CS553 Lecture Introduction to Data-flow Analysis 1

CS553 Lecture Introduction to Data-flow Analysis 1 ! Ide Introdution to Dt-flow nlysis!lst Time! Implementing Mrk nd Sweep GC!Tody! Control flow grphs! Liveness nlysis! Register llotion CS553 Leture Introdution to Dt-flow Anlysis 1 Dt-flow Anlysis! Dt-flow

More information

MTH 146 Conics Supplement

MTH 146 Conics Supplement 105- Review of Conics MTH 146 Conics Supplement In this section we review conics If ou ne more detils thn re present in the notes, r through section 105 of the ook Definition: A prol is the set of points

More information

Agilent G3314AA BioConfirm Software

Agilent G3314AA BioConfirm Software Agilent G3314AA BioConfirm Softwre Quik Strt Guide Use this guide to instll nd get strted with the BioConfirm softwre. Wht is BioConfirm Softwre? Agilent G3314AA BioConfirm Softwre lets you onfirm the

More information

VSxF-2/-3/-4 SMALL LINEAR VALVES PN16 FOR MODULATING AND ON/OFF-CONTROL SPECIFICATIONS

VSxF-2/-3/-4 SMALL LINEAR VALVES PN16 FOR MODULATING AND ON/OFF-CONTROL SPECIFICATIONS VSxF2/3/4 SMLL LINER VLVES PN16 FOR MODULTING ND ON/OFFCONTROL VSxF2 VSxF3 VSxF4 GENERL These smll liner vlves re used in omintion with smll eletri liner vlve tutors nd thermoeletri tutors for the ontrol

More information

[SYLWAN., 158(6)]. ISI

[SYLWAN., 158(6)]. ISI The proposl of Improved Inext Isomorphi Grph Algorithm to Detet Design Ptterns Afnn Slem B-Brhem, M. Rizwn Jmeel Qureshi Fulty of Computing nd Informtion Tehnology, King Adulziz University, Jeddh, SAUDI

More information

An Approach to Filter the Test Data for Killing Multiple Mutants in Different Locations

An Approach to Filter the Test Data for Killing Multiple Mutants in Different Locations Interntionl Journl of Computer Theory nd Engineering, Vol. 5, No. 2, April 2013 An Approh to Filter the Test Dt for Killing Multiple Mutnts in Different Lotions Ngendr Prtp Singh, Rishi Mishr, Silesh Tiwri,

More information

Introduction to Integration

Introduction to Integration Introduction to Integrtion Definite integrls of piecewise constnt functions A constnt function is function of the form Integrtion is two things t the sme time: A form of summtion. The opposite of differentition.

More information

IMAGE COMPRESSION USING HIRARCHICAL LINEAR POLYNOMIAL CODING

IMAGE COMPRESSION USING HIRARCHICAL LINEAR POLYNOMIAL CODING Rsh Al-Tmimi et l, Interntionl Journl of Computer Siene nd Mobile Computing, Vol.4 Issue.1, Jnury- 015, pg. 11-119 Avilble Online t www.ijsm.om Interntionl Journl of Computer Siene nd Mobile Computing

More information

The User-defined Modeling Method of Power System Components Based on RTDS-CBuilder

The User-defined Modeling Method of Power System Components Based on RTDS-CBuilder Energy nd Power Engineering, 2013, 5, 527-533 doi:10.4236/epe.2013.54b101 Published Online July 2013 (http://www.sirp.org/journl/epe) he User-deined Modeling Method o Power System Components Bsed on RDS-CBuilder

More information

Geometrical reasoning 1

Geometrical reasoning 1 MODULE 5 Geometril resoning 1 OBJECTIVES This module is for study y n individul teher or group of tehers. It: looks t pprohes to developing pupils visulistion nd geometril resoning skills; onsiders progression

More information

Internet Routing. IP Packet Format. IP Fragmentation & Reassembly. Principles of Internet Routing. Computer Networks 9/29/2014.

Internet Routing. IP Packet Format. IP Fragmentation & Reassembly. Principles of Internet Routing. Computer Networks 9/29/2014. omputer Networks 9/29/2014 IP Pket Formt Internet Routing Ki Shen IP protool version numer heder length (words) for qulity of servie mx numer remining hops (deremented t eh router) upper lyer protool to

More information

Midterm Exam CSC October 2001

Midterm Exam CSC October 2001 Midterm Exm CSC 173 23 Otoer 2001 Diretions This exm hs 8 questions, severl of whih hve suprts. Eh question indites its point vlue. The totl is 100 points. Questions 5() nd 6() re optionl; they re not

More information

INTEGRATED WORKFLOW ART DIRECTOR

INTEGRATED WORKFLOW ART DIRECTOR ART DIRECTOR Progrm Resoures INTEGRATED WORKFLOW PROGRAM PLANNING PHASE In this workflow phse proess, you ollorte with the Progrm Mnger, the Projet Mnger, nd the Art Speilist/ Imge Led to updte the resoures

More information

THE DYNAMIC MODELING OF A SUBSYSTEM FOR THE UPPER SUPPORTING STRUCTURE OF A BUCKET WHEEL EXCAVATOR

THE DYNAMIC MODELING OF A SUBSYSTEM FOR THE UPPER SUPPORTING STRUCTURE OF A BUCKET WHEEL EXCAVATOR ANNALS of Fulty Engineering Hunedor Interntionl Journl of Engineering Tome XIV [06] Fsiule [Februry] ISSN: 584-665 [print; online] ISSN: 584-67 [CD-Rom; online] free-ess multidisiplinry publition of the

More information

Single-Layer Trunk Routing Using 45-Degree Lines within Critical Areas for PCB Routing

Single-Layer Trunk Routing Using 45-Degree Lines within Critical Areas for PCB Routing SASIMI 2010 Proeedings (R3-8) Single-Lyer Trunk Routing Using 45-Degree Lines within Critil Ares for PCB Routing Kyosuke SHINODA Yukihide KOHIRA Atsushi TAKAHASHI Tokyo Institute of Tehnology Dept. of

More information

To access your mailbox from inside your organization. For assistance, call:

To access your mailbox from inside your organization. For assistance, call: 2001 Ative Voie, In. All rights reserved. First edition 2001. Proteted y one or more of the following United Sttes ptents:,070,2;,3,90;,88,0;,33,102;,8,0;,81,0;,2,7;,1,0;,90,88;,01,11. Additionl U.S. nd

More information

APPLICATIONS OF INTEGRATION

APPLICATIONS OF INTEGRATION Chpter 3 DACS 1 Lok 004/05 CHAPTER 5 APPLICATIONS OF INTEGRATION 5.1 Geometricl Interprettion-Definite Integrl (pge 36) 5. Are of Region (pge 369) 5..1 Are of Region Under Grph (pge 369) Figure 5.7 shows

More information

Chapter 4 Fuzzy Graph and Relation

Chapter 4 Fuzzy Graph and Relation Chpter 4 Fuzzy Grph nd Reltion Grph nd Fuzzy Grph! Grph n G = (V, E) n V : Set of verties(node or element) n E : Set of edges An edge is pir (x, y) of verties in V.! Fuzzy Grph ~ n ( ~ G = V, E) n V :

More information

FEEDBACK: The standard error of a regression is not an unbiased estimator for the standard deviation of the error in a multiple regression model.

FEEDBACK: The standard error of a regression is not an unbiased estimator for the standard deviation of the error in a multiple regression model. Introutory Eonometris: A Moern Approh 6th Eition Woolrige Test Bnk Solutions Complete ownlo: https://testbnkre.om/ownlo/introutory-eonometris-moern-pproh-6th-eition-jeffreym-woolrige-test-bnk/ Solutions

More information

Right Angled Trigonometry. Objective: To know and be able to use trigonometric ratios in rightangled

Right Angled Trigonometry. Objective: To know and be able to use trigonometric ratios in rightangled C2 Right Angled Trigonometry Ojetive: To know nd e le to use trigonometri rtios in rightngled tringles opposite C Definition Trigonometry ws developed s method of mesuring ngles without ngulr units suh

More information

Doubts about how to use azimuth values from a Coordinate Object. Juan Antonio Breña Moral

Doubts about how to use azimuth values from a Coordinate Object. Juan Antonio Breña Moral Douts out how to use zimuth vlues from Coordinte Ojet Jun Antonio Breñ Morl # Definition An Azimuth is the ngle from referene vetor in referene plne to seond vetor in the sme plne, pointing towrd, (ut

More information

P(r)dr = probability of generating a random number in the interval dr near r. For this probability idea to make sense we must have

P(r)dr = probability of generating a random number in the interval dr near r. For this probability idea to make sense we must have Rndom Numers nd Monte Crlo Methods Rndom Numer Methods The integrtion methods discussed so fr ll re sed upon mking polynomil pproximtions to the integrnd. Another clss of numericl methods relies upon using

More information

THE THEORY AND APPLICATION OF STRUCTURED LIGHT PHOTOGRAMMETRY WITH KNOWN ANGLE

THE THEORY AND APPLICATION OF STRUCTURED LIGHT PHOTOGRAMMETRY WITH KNOWN ANGLE THE THEOR AD APPICATIO OF TRUCTURED IGHT PHOTOGRAMMETR WITH KOW AGE i in * Hou Wengung hng Holing hool o Remote ensing nd Inormtion Engineering Wuhn Universit 9 uou Rod Wuhn Chin - li6@gmil.om -houwengung99@6.om

More information

10.5 Graphing Quadratic Functions

10.5 Graphing Quadratic Functions 0.5 Grphing Qudrtic Functions Now tht we cn solve qudrtic equtions, we wnt to lern how to grph the function ssocited with the qudrtic eqution. We cll this the qudrtic function. Grphs of Qudrtic Functions

More information

and vertically shrinked by

and vertically shrinked by 1. A first exmple 1.1. From infinite trnsltion surfe mp to end-periodi mp. We begin with n infinite hlf-trnsltion surfe M 0 desribed s in Figure 1 nd n ffine mp f 0 defined s follows: the surfe is horizontlly

More information

COSC 6374 Parallel Computation. Non-blocking Collective Operations. Edgar Gabriel Fall Overview

COSC 6374 Parallel Computation. Non-blocking Collective Operations. Edgar Gabriel Fall Overview COSC 6374 Prllel Computtion Non-loking Colletive Opertions Edgr Griel Fll 2014 Overview Impt of olletive ommunition opertions Impt of ommunition osts on Speedup Crtesin stenil ommunition All-to-ll ommunition

More information

CS453 INTRODUCTION TO DATAFLOW ANALYSIS

CS453 INTRODUCTION TO DATAFLOW ANALYSIS CS453 INTRODUCTION TO DATAFLOW ANALYSIS CS453 Leture Register llotion using liveness nlysis 1 Introdution to Dt-flow nlysis Lst Time Register llotion for expression trees nd lol nd prm vrs Tody Register

More information

MITSUBISHI ELECTRIC RESEARCH LABORATORIES Cambridge, Massachusetts. Introduction to Matroids and Applications. Srikumar Ramalingam

MITSUBISHI ELECTRIC RESEARCH LABORATORIES Cambridge, Massachusetts. Introduction to Matroids and Applications. Srikumar Ramalingam Cmrige, Msshusetts Introution to Mtrois n Applitions Srikumr Rmlingm MERL mm//yy Liner Alger (,0,0) (0,,0) Liner inepenene in vetors: v, v2,..., For ll non-trivil we hve s v s v n s, s2,..., s n 2v2...

More information

Unit 5 Vocabulary. A function is a special relationship where each input has a single output.

Unit 5 Vocabulary. A function is a special relationship where each input has a single output. MODULE 3 Terms Definition Picture/Exmple/Nottion 1 Function Nottion Function nottion is n efficient nd effective wy to write functions of ll types. This nottion llows you to identify the input vlue with

More information

TEMPLATE FOR ENTRY in Encyclopedia of Database Systems: GRID FILE. Yannis Manolopoulos

TEMPLATE FOR ENTRY in Encyclopedia of Database Systems: GRID FILE. Yannis Manolopoulos TEMPLATE FOR ENTRY in Enylopedi of Dtse Systems: GRID FILE Apostolos N. Ppdopoulos Ynnis Mnolopoulos Ynnis Theodoridis Vssilis Tsotrs Deprtment of Informtis Aristotle University of Thessloniki Thessloniki,

More information

Mixed-Signal Testability Analysis for Data-Converter IPs

Mixed-Signal Testability Analysis for Data-Converter IPs Mixed-Signl Testility Anlysis for Dt-Converter IPs Arldo vn de Krts nd Hns G. Kerkhoff Testle Design nd Testing of Nnosystems Group MESA+ Institute for Nnotehnology 7500AE Enshede, the Netherlnds Emil:

More information

Selecting the Most Highly Correlated Pairs within a Large Vocabulary

Selecting the Most Highly Correlated Pairs within a Large Vocabulary Seleting the Most Highl Correlted Pirs within Lrge Voulr Koji Umemur Deprtment of Computer Siene Toohshi Universit of Tehnolog umemur@tutistutjp Astrt Ourene ptterns of words in douments n e epressed s

More information

LINX MATRIX SWITCHERS FIRMWARE UPDATE INSTRUCTIONS FIRMWARE VERSION

LINX MATRIX SWITCHERS FIRMWARE UPDATE INSTRUCTIONS FIRMWARE VERSION Overview LINX MATRIX SWITCHERS FIRMWARE UPDATE INSTRUCTIONS FIRMWARE VERSION 4.4.1.0 Due to the omplex nture of this updte, plese fmilirize yourself with these instrutions nd then ontt RGB Spetrum Tehnil

More information

Troubleshooting. Verify the Cisco Prime Collaboration Provisioning Installation (for Advanced or Standard Mode), page

Troubleshooting. Verify the Cisco Prime Collaboration Provisioning Installation (for Advanced or Standard Mode), page Trouleshooting This setion explins the following: Verify the Ciso Prime Collortion Provisioning Instlltion (for Advned or Stndrd Mode), pge 1 Upgrde the Ciso Prime Collortion Provisioning from Smll to

More information

Chapter Spline Method of Interpolation More Examples Electrical Engineering

Chapter Spline Method of Interpolation More Examples Electrical Engineering Chpter. Spline Method of Interpoltion More Exmples Electricl Engineering Exmple Thermistors re used to mesure the temperture of bodies. Thermistors re bsed on mterils chnge in resistnce with temperture.

More information

Comparison between nmos Pass Transistor logic style vs. CMOS Complementary Cells*

Comparison between nmos Pass Transistor logic style vs. CMOS Complementary Cells* Comprison etween nmos Pss Trnsistor logi style vs. CMOS Complementry Cells* Rkesh Mehrotr, Mssoud Pedrm Xunwei Wu Dept. of E.E.-Systems Dept. of Eletroni Eng. University of Southern Cliforni Hngzhou University

More information

6.3 Volumes. Just as area is always positive, so is volume and our attitudes towards finding it.

6.3 Volumes. Just as area is always positive, so is volume and our attitudes towards finding it. 6.3 Volumes Just s re is lwys positive, so is volume nd our ttitudes towrds finding it. Let s review how to find the volume of regulr geometric prism, tht is, 3-dimensionl oject with two regulr fces seprted

More information

1.5 Extrema and the Mean Value Theorem

1.5 Extrema and the Mean Value Theorem .5 Extrem nd the Men Vlue Theorem.5. Mximum nd Minimum Vlues Definition.5. (Glol Mximum). Let f : D! R e function with domin D. Then f hs n glol mximum vlue t point c, iff(c) f(x) for ll x D. The vlue

More information

WORKSHOP 9 HEX MESH USING SWEEP VECTOR

WORKSHOP 9 HEX MESH USING SWEEP VECTOR WORKSHOP 9 HEX MESH USING SWEEP VECTOR WS9-1 WS9-2 Prolem Desription This exerise involves importing urve geometry from n IGES file. The urves re use to rete other urves. From the urves trimme surfes re

More information

McAfee Network Security Platform

McAfee Network Security Platform NS3x00 Quik Strt Guide Revision B MAfee Network Seurity Pltform This quik strt guide explins how to quikly set up nd tivte your MAfee Network Seurity Pltform NS3100 nd NS3200 Sensors in inline mode. These

More information

Containers: Queue and List

Containers: Queue and List Continers: Queue n List Queue A ontiner in whih insertion is one t one en (the til) n eletion is one t the other en (the he). Also lle FIFO (First-In, First-Out) Jori Cortell n Jori Petit Deprtment of

More information

V = set of vertices (vertex / node) E = set of edges (v, w) (v, w in V)

V = set of vertices (vertex / node) E = set of edges (v, w) (v, w in V) Definitions G = (V, E) V = set of verties (vertex / noe) E = set of eges (v, w) (v, w in V) (v, w) orere => irete grph (igrph) (v, w) non-orere => unirete grph igrph: w is jent to v if there is n ege from

More information

CS 551 Computer Graphics. Hidden Surface Elimination. Z-Buffering. Basic idea: Hidden Surface Removal

CS 551 Computer Graphics. Hidden Surface Elimination. Z-Buffering. Basic idea: Hidden Surface Removal CS 55 Computer Grphis Hidden Surfe Removl Hidden Surfe Elimintion Ojet preision lgorithms: determine whih ojets re in front of others Uses the Pinter s lgorithm drw visile surfes from k (frthest) to front

More information

Lecture 8: Graph-theoretic problems (again)

Lecture 8: Graph-theoretic problems (again) COMP36111: Advned Algorithms I Leture 8: Grph-theoreti prolems (gin) In Prtt-Hrtmnn Room KB2.38: emil: iprtt@s.mn..uk 2017 18 Reding for this leture: Sipser: Chpter 7. A grph is pir G = (V, E), where V

More information

Math 464 Fall 2012 Notes on Marginal and Conditional Densities October 18, 2012

Math 464 Fall 2012 Notes on Marginal and Conditional Densities October 18, 2012 Mth 464 Fll 2012 Notes on Mrginl nd Conditionl Densities klin@mth.rizon.edu October 18, 2012 Mrginl densities. Suppose you hve 3 continuous rndom vribles X, Y, nd Z, with joint density f(x,y,z. The mrginl

More information

c s ha2 c s Half Adder Figure 2: Full Adder Block Diagram

c s ha2 c s Half Adder Figure 2: Full Adder Block Diagram Adder Tk: Implement 2-it dder uing 1-it full dder nd 1-it hlf dder omponent (Figure 1) tht re onneted together in top-level module. Derie oth omponent in VHDL. Prepre two implementtion where VHDL omponent

More information

the machine and check the components AC Power Cord Carrier Sheet/ Plastic Card Carrier Sheet DVD-ROM

the machine and check the components AC Power Cord Carrier Sheet/ Plastic Card Carrier Sheet DVD-ROM Quik Setup Guide Strt Here ADS-2100 Plese red the Produt Sfety Guide first efore you set up your mhine. Then, plese red this Quik Setup Guide for the orret setup nd instlltion. WARNING WARNING indites

More information

Distance vector protocol

Distance vector protocol istne vetor protool Irene Finohi finohi@i.unirom.it Routing Routing protool Gol: etermine goo pth (sequene of routers) thru network from soure to Grph strtion for routing lgorithms: grph noes re routers

More information

SOFTWARE-BUG LOCALIZATION WITH GRAPH MINING

SOFTWARE-BUG LOCALIZATION WITH GRAPH MINING Chpter 17 SOFTWARE-BUG LOCALIZATION WITH GRAPH MINING Frnk Eihinger Institute for Progrm Strutures nd Dt Orgniztion (IPD) Universit-t Krlsruhe (TH), Germny eihinger@ipd.uk.de Klemens B-ohm Institute for

More information

Image Compression based on Quadtree and Polynomial

Image Compression based on Quadtree and Polynomial Interntionl Journl of Computer Applitions (0975 8887 Imge Compression sed on Qudtree nd Polynomil Ghdh Al-Khfj Ph.D Dept. of Computer Siene, Bghdd University, College of Siene. ABSTRACT In this pper, n

More information

An Efficient 8b/10b Encoder and Decoder Design using Reversible Logic Gates

An Efficient 8b/10b Encoder and Decoder Design using Reversible Logic Gates Interntionl Journl of Eletril Eletronis & Computer Siene Engineering Volume 4, Issue 6 (Deemer, 207) E-ISSN : 2348-2273 P-ISSN : 2454-222 Aville Online t www.ijeese.om An Effiient 8/0 Enoder nd Deoder

More information

High-performance Monitoring Software. User s Manual

High-performance Monitoring Software. User s Manual High-performne Monitoring Softwre User s Mnul Introdution Thnk you for purhsing WeView Livesope MV Ver. 2.1. Plese red this mnul prior to use to ensure tht you will e le to use this softwre effetively.

More information

Agilent MassHunter Workstation Data Acquisition for 6400 Series Triple Quadrupole LC/MS Familiarization Guide

Agilent MassHunter Workstation Data Acquisition for 6400 Series Triple Quadrupole LC/MS Familiarization Guide Agilent MssHunter Worksttion Dt Aquisition for 6400 Series Triple Qudrupole LC/MS Fmiliriztion Guide Before you egin 3 Prepre your system 3 Prepre to quire dt 4 Exerise 1 Develop n quisition method 6 Tsk

More information

UT1553B BCRT True Dual-port Memory Interface

UT1553B BCRT True Dual-port Memory Interface UTMC APPICATION NOTE UT553B BCRT True Dul-port Memory Interfce INTRODUCTION The UTMC UT553B BCRT is monolithic CMOS integrted circuit tht provides comprehensive MI-STD- 553B Bus Controller nd Remote Terminl

More information

Greedy Algorithm. Algorithm Fall Semester

Greedy Algorithm. Algorithm Fall Semester Greey Algorithm Algorithm 0 Fll Semester Optimiztion prolems An optimiztion prolem is one in whih you wnt to fin, not just solution, ut the est solution A greey lgorithm sometimes works well for optimiztion

More information

Lesson 4.4. Euler Circuits and Paths. Explore This

Lesson 4.4. Euler Circuits and Paths. Explore This Lesson 4.4 Euler Ciruits nd Pths Now tht you re fmilir with some of the onepts of grphs nd the wy grphs onvey onnetions nd reltionships, it s time to egin exploring how they n e used to model mny different

More information

Section 10.4 Hyperbolas

Section 10.4 Hyperbolas 66 Section 10.4 Hyperbols Objective : Definition of hyperbol & hyperbols centered t (0, 0). The third type of conic we will study is the hyperbol. It is defined in the sme mnner tht we defined the prbol

More information

1.1. Interval Notation and Set Notation Essential Question When is it convenient to use set-builder notation to represent a set of numbers?

1.1. Interval Notation and Set Notation Essential Question When is it convenient to use set-builder notation to represent a set of numbers? 1.1 TEXAS ESSENTIAL KNOWLEDGE AND SKILLS Prepring for 2A.6.K, 2A.7.I Intervl Nottion nd Set Nottion Essentil Question When is it convenient to use set-uilder nottion to represent set of numers? A collection

More information

COSC 6374 Parallel Computation. Dense Matrix Operations

COSC 6374 Parallel Computation. Dense Matrix Operations COSC 6374 Prllel Computtion Dense Mtrix Opertions Edgr Griel Fll Edgr Griel Prllel Computtion Edgr Griel erminology Dense Mtrix: ll elements of the mtrix ontin relevnt vlues ypilly stored s 2-D rry, (e.g.

More information

Engineer To Engineer Note

Engineer To Engineer Note Engineer To Engineer Note EE-169 Technicl Notes on using Anlog Devices' DSP components nd development tools Contct our technicl support by phone: (800) ANALOG-D or e-mil: dsp.support@nlog.com Or visit

More information

Minimal Memory Abstractions

Minimal Memory Abstractions Miniml Memory Astrtions (As implemented for BioWre Corp ) Nthn Sturtevnt University of Alert GAMES Group Ferury, 7 Tlk Overview Prt I: Building Astrtions Minimizing memory requirements Performnes mesures

More information

A Fast Delay Analysis Algorithm for The Hybrid Structured Clock Network

A Fast Delay Analysis Algorithm for The Hybrid Structured Clock Network A Fst Dely Anlysis Algorithm for The Hyrid Strutured Clok Network Yi Zou 1, Yii Ci 1,Qing Zhou 1,Xinlong Hong 1, Sheldon X.-D. Tn 2 1 Deprtment of Computer Siene nd Tehnology, Tsinghu University, Beijing,

More information

GENERATING ORTHOIMAGES FOR CLOSE-RANGE OBJECTS BY AUTOMATICALLY DETECTING BREAKLINES

GENERATING ORTHOIMAGES FOR CLOSE-RANGE OBJECTS BY AUTOMATICALLY DETECTING BREAKLINES GENEATING OTHOIMAGES FO CLOSE-ANGE OBJECTS BY AUTOMATICALLY DETECTING BEAKLINES Efstrtios Stylinidis 1, Lzros Sechidis 1, Petros Ptis 1, Spiros Sptls 2 Aristotle University of Thessloniki 1 Deprtment of

More information

Shared Memory Architectures. Programming and Synchronization. Today s Outline. Page 1. Message passing review Cosmic Cube discussion

Shared Memory Architectures. Programming and Synchronization. Today s Outline. Page 1. Message passing review Cosmic Cube discussion Tody s Outline Arhitetures Progrmming nd Synhroniztion Disuss pper on Cosmi Cube (messge pssing) Messge pssing review Cosmi Cube disussion > Messge pssing mhine Shred memory model > Communition > Synhroniztion

More information

The Network Layer: Routing in the Internet. The Network Layer: Routing & Addressing Outline

The Network Layer: Routing in the Internet. The Network Layer: Routing & Addressing Outline CPSC 852 Internetworking The Network Lyer: Routing in the Internet Mihele Weigle Deprtment of Computer Siene Clemson University mweigle@s.lemson.edu http://www.s.lemson.edu/~mweigle/ourses/ps852 1 The

More information

COSC 6374 Parallel Computation. Communication Performance Modeling (II) Edgar Gabriel Fall Overview. Impact of communication costs on Speedup

COSC 6374 Parallel Computation. Communication Performance Modeling (II) Edgar Gabriel Fall Overview. Impact of communication costs on Speedup COSC 6374 Prllel Computtion Communition Performne Modeling (II) Edgr Griel Fll 2015 Overview Impt of ommunition osts on Speedup Crtesin stenil ommunition All-to-ll ommunition Impt of olletive ommunition

More information

Enterprise Digital Signage Create a New Sign

Enterprise Digital Signage Create a New Sign Enterprise Digitl Signge Crete New Sign Intended Audiene: Content dministrtors of Enterprise Digitl Signge inluding stff with remote ess to sign.pitt.edu nd the Content Mnger softwre pplition for their

More information

Complete Coverage Path Planning of Mobile Robot Based on Dynamic Programming Algorithm Peng Zhou, Zhong-min Wang, Zhen-nan Li, Yang Li

Complete Coverage Path Planning of Mobile Robot Based on Dynamic Programming Algorithm Peng Zhou, Zhong-min Wang, Zhen-nan Li, Yang Li 2nd Interntionl Conference on Electronic & Mechnicl Engineering nd Informtion Technology (EMEIT-212) Complete Coverge Pth Plnning of Mobile Robot Bsed on Dynmic Progrmming Algorithm Peng Zhou, Zhong-min

More information

2 Computing all Intersections of a Set of Segments Line Segment Intersection

2 Computing all Intersections of a Set of Segments Line Segment Intersection 15-451/651: Design & Anlysis of Algorithms Novemer 14, 2016 Lecture #21 Sweep-Line nd Segment Intersection lst chnged: Novemer 8, 2017 1 Preliminries The sweep-line prdigm is very powerful lgorithmic design

More information

Polygonal Approximation of Voronoi Diagrams of a Set of Triangles in Three Dimensions Marek Teichmann Seth Teller MIT Computer Graphics Group Abstract

Polygonal Approximation of Voronoi Diagrams of a Set of Triangles in Three Dimensions Marek Teichmann Seth Teller MIT Computer Graphics Group Abstract Polygonl Approximtion of Voronoi Digrms of Set of Tringles in Three Dimensions Mrek Teihmnn Seth Teller MIT Computer Grphis Group Astrt We desrie roust dptive mrhing tetrhedr type lgorithm for onstruting

More information

Compiling a Parallel DSL to GPU

Compiling a Parallel DSL to GPU Compiling Prllel DSL to GPU Rmesh Nrynswmy Bdri Gopln Synopsys In. Synopsys 2012 1 Agend Overview of Verilog Simultion Prllel Verilog Simultion Algorithms Prllel Simultion Trdeoffs on GPU Chllenges Synopsys

More information

Representation of Numbers. Number Representation. Representation of Numbers. 32-bit Unsigned Integers 3/24/2014. Fixed point Integer Representation

Representation of Numbers. Number Representation. Representation of Numbers. 32-bit Unsigned Integers 3/24/2014. Fixed point Integer Representation Representtion of Numbers Number Representtion Computer represent ll numbers, other thn integers nd some frctions with imprecision. Numbers re stored in some pproximtion which cn be represented by fixed

More information

Before We Begin. Introduction to Spatial Domain Filtering. Introduction to Digital Image Processing. Overview (1): Administrative Details (1):

Before We Begin. Introduction to Spatial Domain Filtering. Introduction to Digital Image Processing. Overview (1): Administrative Details (1): Overview (): Before We Begin Administrtive detils Review some questions to consider Winter 2006 Imge Enhncement in the Sptil Domin: Bsics of Sptil Filtering, Smoothing Sptil Filters, Order Sttistics Filters

More information

A New Method for Solving Intuitionistic Fuzzy. Transportation Problem

A New Method for Solving Intuitionistic Fuzzy. Transportation Problem pplied Mtemtil Sienes, Vol 7,, no 8, 57-65 HKR Ltd, wwwm-ikriom New Metod for Solving ntuitionisti Fuzzy Trnsporttion Prolem Ngoor Gni PG & Reser Deprtment of Mtemtis Jml Momed College uto Tiruirpplli-6,

More information