Solving Linear Ordinary Differential Equations using Singly Diagonally Implicit Runge-Kutta fifth order five-stage method
|
|
- Sheila Miles
- 6 years ago
- Views:
Transcription
1 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Solvng Lnear Ordnar Dfferental Equatons usng Sngl Dagonall Implct Runge-Kutta ffth order fve-stage method FUDZIAH ISMAIL, NUR IZZATI CHE JAWIAS, MOHAMED SULEIMAN AND AZMI JAAFAR Department of Mathematcs, Facult of Scence Department of Informaton Sstem, Facult of Computer Scence and Informaton Technolog Unverst Putra Malasa 00, Serdang, Selangor MALAYSIA Abstract: - We constructed a new ffth order fve-stage sngl dagonall mplct Runge-Kutta (DIRK) method whch s specall desgned for the ntegratons of lnear ordnar dfferental equatons (LODEs). The restrcton to lnear ordnar dfferental equatons (ODEs) reduces the number of condtons whch the coeffcents of the Runge-Kutta method must satsf. The best strateg for practcal purposes would be to choose the coeffcents of the Runge-Kutta methods such that the error norm s mnmzed. Thus, here the error norm obtaned from the error equatons of the sxth order method s mnmzed so that the free parameters chosen are obtaned from the mnmzed error norm. The stablt aspect of the method s also looked nto and found to have substantal regon of stablt, thus t s stable. Then a set of test problems are used to valdate the method. Numercal results show that the new method s more effcent n terms of accurac compared to the exstng method. Ke-Words: - Runge-Kutta, Lnear ordnar dfferental equatons, Error norm. Introducton Man algorthms have been proposed for the numercal soluton of ntal value problem f ( x, ), ( x0 ) 0, m f : () Such algorthm s the Sngl Dagonall Implct Runge-Kutta (SDIRK) method whch was ntroduced to overcome some of the lmtatons of full mplct and explct Runge-Kutta method. Prelmnar experments have shown that these methods are usuall more effcent than the standard Sngl Implct Runge-Kutta (SIRK) method and n man cases are compettve wth backward dfferentaton formula. Ths algorthms can be used b both lnear and nonlnear sstems of ordnar equatons. However n ths paper, we consder the numercal ntegraton of lnear nhomogeneous sstems of ordnar dfferental equatons (ODEs) of the form A G(x) () where A s a square matrx whose entres does not depend on or x, and and G(x) are vectors. Such sstems arse n the numercal soluton of partal dfferental equatons (PDEs) governng wave and heat phenomena after applcaton of a spatal dscretzaton such as fnte-dfference method. Ths tpe of partal dfferental equatons can be solved numercall usng methods suggested b Rasulov and Kul [7], Rasulov et. al [8] and Zabala and Ramos []. Actuall there have been several attempts to develop effcent methods for ntegratng lnear sstems of ODEs. The basc concept of ths method s that the maor cost n evaluatng the dervatve functon s n formng the matrx A and vector G(x). ISSN: Issue 8, Volume 8, August 009
2 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Explct Runge-Kutta method s ver popular for smulatons of wave equatons; see Zngg and Chsholm [], due to ther hgh accurac and low memor requrements. To derve Runge-Kutta (RK) methods, we need to fulfll certan order equatons; see Dormand []. These order equatons resulted from the dervatves of the functon f ( x, ) tself. If the functon s lnear then some of the error equatons resulted b the nonlneart n the dervatve functon can be removed, thus less order equatons need to be satsfed, hence a more effcent method n some respect than the classcal method can be derved. In ths paper, we construct dagonall mplct Runge-Kutta method specfcall for lnear ODEs wth constant coeffcents. We consder the prncpal terms of the local truncaton error to mnmze the error norm. Then, a few test equatons are used to valdate the new method. Materals and Methods. Dervaton of the method In ths secton, we consder the followng scalar ODE f ( x, ) () When a general s-stage dagonall mplct Runge-Kutta method s appled to the ODE, the followng equatons are obtaned, Chsholm []. The order equatons are elmnated b explotng the fact that, for lnear ODEs, f x f 0. x Zngg and Chsholm [] too have derved a new explct RK methods whch are sutable for lnear ODEs that are more effcent than the conventonal RK methods. Table : Order equatons for ffth order Runge-Kutta method sutable for LODEs. () b. () b c. () b c. () a c b 6 5. () b c 6. () a c b where k n s h b k () n f ( x c h, h a k ) () n n 7. () a a c b k k k 8. (5) b c 0 We shall alwas assume that the row-sum s condton holds c a, where,..s. Accordng to Dormand [], there are 7 order equatons (error equatons) needed to be satsfed b the ffth order fve-stage RK method. The restrcton to lnear ODEs reduces the number of equatons whch the coeffcents of the RK method must satsf see Zngg and 9. (5) a c 5 6 b 0 0. (5) a a c 8 b k k 0 k. (5) a a a c 9 b k km m 0 km ISSN: Issue 8, Volume 8, August 009
3 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Usng the smplfng assumpton: b a b c ),,...,5 (5) We have ( 5. a a a c 9 b k km m 60 km 6. a a a a c 0 b k km mn n 70 kmn b a c ( 6 b c ) ( b c ), thus equaton can be removed, smlarl we can remove equatons 6 and 9 n table. Thus, usng (5) the order equatons are replaced b smpler equatons. The are: b a ba b5a5 b ( c ba b5a5 b ( c b5a5 b ( c 5 c5 ) ) ) Altogether there are equatons needed to be satsfed and we have 5 unknowns. So, we can have four free parameters whch are chosen to be c, c, c and. Solvng whch, we have all equatons n terms of c, c c and., The order equatons for the sxth order method are the order equatons n table and the addtonal order equatons gven n table. as obtaned b Zngg and Chsholm []. Table : Addtonal order equatons for sxth order Runge-Kutta method 5. c b 6. a c 7 b 0. a a c 5 b k k 0 km In order to choose the free parameters c, c, c and, the prncpal terms of the local truncaton error must be consdered. Usng the error functon p n p ( p) ( p) and RK error coeffcents [], the prncpal term for ffth order method s 5 6 F F The best strateg for practcal purposes would be to choose the free RK parameters s to mnmze the error norm, see Dormand []; ( p) ( p) n p ( ( p) So we have the prncpal error norm for ths method; ( ) ( 7 ) ( 5 ) ( 9 ) ( 0) where are the error equatons assocated wth the sxth order method, (n table ). Substtutng the free parameters nto A, we obtaned the prncpal error norm n terms of c,c and., c Mnmzng the error norm, we have c , c , c and Substtutng the values of c, c, c and and solvng all the equatons we fnall get all the coeffcents of the new SDIRK method for LODEs as follows; ) ISSN: Issue 8, Volume 8, August 009
4 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar c c c c a a a a f ( x, ) R( h ) R( hˆ) hb ˆ ( I ha ˆ ) T where A s (m x m), e s (m x ) are obtaned from the method tself and R(hˆ) s called the stablt polnomal of the method. The stablt regon s obtaned b takng R( hˆ) cos sn. Usng the MATHEMATICA package we obtaned the stablt polnomal and also the stablt regon. The stablt polnomal for new ffth order fve-stage SDIRK method s e a a a a a a b b b b b c a a a a a55. Stablt One of the practcal crtera for a good method to be useful s that t must have regon of absolute stablt. When an s-stage Runge-Kutta method (equatons () and ()) s appled to the test equaton, R (hˆ) hˆ 0.00hˆ 0.06hˆ 0.00hˆ hˆ hˆ 0.066hˆ 0.007hˆ hˆ hˆ hˆ 0.008hˆ 0.000hˆ hˆ hˆ 0.00hˆ hˆ hˆ hˆ hˆ hˆ hˆ 0.05hˆ 0.007hˆ hˆ hˆ 0.095hˆ 0.00hˆ hˆ hˆ 0.058hˆ hˆ 0.000hˆ hˆ 0.06hˆ hˆ hˆ hˆ 0.07hˆ 0.05hˆ 0.000hˆ hˆ hˆ 0.070hˆ 0.005hˆ wth value of ; ISSN: Issue 8, Volume 8, August 009
5 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar where ˆ ˆ h h ˆ h ˆ ˆ5 h h. The stablt polnomal s solve for ĥ whch gves the value of R ( h ˆ) ; ths s done b usng Mathematca package (see Torrence []). The stablt regon s obtaned b tracng the values of ĥ and s shown n Fgure. Where the vertcal axs s the magnar part and the horzontal axs s the real part. where R ( hˆ) hˆ( hˆ 0.0 ( 0.08 hˆ ˆ ˆ ˆ h ) 0.7 (0.0 h 0.7 h ) ˆ ˆ (0.7 h h ) ( ˆ ˆ ˆ h h h ) 0.70 (0.60 ˆ 0.08 ˆ ˆ h h h ) 0.70 ( ˆ ˆ ˆ h h h ˆ h )) ImagnarPart 7.5 StabltRegon Equatng ˆ) (h R cos sn and solvng for h we have the stablt regon of the method. 5.5 Imagnar Part StabltRegon Real Part - Fgu re : The stablt regon for the 5 th order 5-stage SDIRK method Real Part The stablt analss for ffth order fve-stage explct Runge-Kutta () method whch has been derved b Zngg and Chsholm [] s dscussed below; Where the stablt polnomal s obtaned as n the SDIRK method and the stablt polnomal for the explct method s denoted b R h, Fgure 5.: The stablt regon for method Clearl the mplct method has bgger regon of stablt compared to the explct method and hence more stable. ISSN: Issue 8, Volume 8, August 009
6 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Results and Dscusson We use the method to obtan the numercal solutons to the followng problems, all of them are lnear ODEs. Exact Soluton: PROLEM : ' ( t) tan t ( t) cos t sn t Source: J. C. utcher [ ] PROLEM : t t '( ) t e t t ( t) t ( e e) t 5, () 0 Source: urden and Fares []. PROLEM : ( 0), (0) 0, [0,0] Exact Soluton: cos t 0 t, (0) Source: Tam [0] PROL EM 5: 5 ( 0) 0, (0) 0 (0), [0, ] Exact Soluton: ( x) cos( x) 6sn( x) 6x ( x) sn( x) 6 cos( x) 6 ( x) sn( x) cos( x) Source: Flowers [6] PROLEM : Source: Suleman [9] PR OLEM 6: ( 0) 0, (0), [0,5] ISSN: Issue 8, Volume 8, August 009
7 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Exact Soluto n: ( x) xe x T able : Numercal results for problem ( x) ( x) e x MTHD H MAXE Source: ronson [] The numercal results are tabulated and compared wth the exstng method and below are the notatons used: H ~ Step sze used MTHD ~ Method emploed MAXE ~Maxmum error The true soluton mnus the computed soluton ( x ) : ~ New ffth order fvestage SDIRK method wth mnmzed error norm for LODEs. ~ Ffth order fve-stage explct RK method for LODEs (Zngg and Chsholm, []) SDIRK(II)~ Optmal fourth order fve-stage SDIRK (Ferracna and Spker, [5]) e-009. ERK 5.75e e e-0. ERK e e e-0. ERK e e e-0. ERK e e e ERK e e e-0 6. ERK e e e e e-0 ISSN: Issue 8, Volume 8, August 009
8 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Ta ble : Numercal results for pro blem MTHD MAXE.695e e e e e e e e-00.05e e e-00.80e e e-00.98e e e e e e-00.09e e-009.9e-006.6e-009 Ta ble 6: Numercal resu lts for pro blem e e e-009 MTHD H. 0. MAXE.0e e e e-00.0e e e e e e-00.97e e e e-00.58e-00 Table 5: Numercal results for problem MTHD H MAXE.060e e e e e e-0.05e e-0.5e e e e e e e e e e e e e-0 ISSN: Issue 8, Volume 8, August 009
9 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar Table 7: Numercal results for proble m 5 MTHD H MAXE e-0.066e e L SDIRK(II).0e e e e e-0.876e e e-008 SDIRK(II) 5.866e SDIRKL e-0.77e e e-0 L e-00 SDIRK(II).58e e e e SDIRK5l.067e L.896e-0 SDIRK(II) 9.70e-0.05e L.009e-0 SDIRK(II).5e e e-05 SDIRK(II) e e e-06 SDIRK(II) 6.888e-0 Concluson The new ffth order fve-stage SDIRK method wth mnmzed error norm has been presented for the ntegraton of lnear ODEs. It has a substantal regon of stablt, thus, t s stable. From the numercal results gven n Table -8, and for all the problems tested, we can conclude that the new ffth order fve-stage SDIRK method whch s sutable for lnear ODEs performs better n terms of maxmum error compared to the ffth order fve-stage ERK method and the optmal fourth order fve-stage SDIRK method. Table 8: Numercal results for problem 6 H MAXE MTHD.6e e e e e e e e e-007 References [] ronson R. Modern Introductor Dfferental Equaton, Schaum s Outlne Seres. USA: McGraw-Hll 97. [] urden R.L., Fares J.D. Numercal Analss seventh edton, Wadsworth Group. rooks/cole, Thomson Learnng, Inc. 00 [] utcher J.C. Numercal Methods for Ordnar Dfferental Equaton, John Wle & Sons Ltd. 00 [] Dormand J.R. Numercal Methods for Dfferental Equatons, oca Raton, New York, London and Toko: CRC Press, Inc ISSN: Issue 8, Volume 8, August 009
10 Fudzah Ismal, Nur Izzat Che Jawas, Mohamed Suleman, Azm Jaafar [6] Flowers,. H An Introducton to Numercal Methods n C+ +, New York: Unverst Oxford Press 000. [7] Rasulov, R and Kul, R. H. Numercal Soluton of One Dmensonal Nonlnear Wave Equaton wth Twce Nonlneart n a class of Dscontnuous Functons, WSEAS Transactons on Mathematcs, vol 5, no, 006, : 6-8. [8] Rasulov, M, Snsoal,. and Hata, S. Numercal Smulaton and Intal-oundar Value Problems for Traffc Flow n a class of Dscontnuous Functons, WSEAS Transactons on Mathematcs, vol 5, no, 006, : 9-. [9] Suleman M.. Solvng Hgher Order ODEs Drectl b Drect Integraton Method, Appled Math. And Computaton. (), 989: [0] Tam, H. W. Two-stage Parallel Methods for the Numercal Soluton of Ordnar Dfferental Equatons, Sam J. Sc. Stat. Comput. (5, 99: [] Torrence.F., Torrence E.A.: How to fnd the stablt regons, The Student s Introducton to Mathematca, 999, pp. -6. [] Zabala, D. and Ramos, A. L. Effect of the Fnte Dfference Soluton Scheme n a Free oundar Convectve Mass Transfer Model, WSEAS Transactons on Mathematcs, vol 6, no 6, 007, : [5] Ferracna L., Spker M.N. Strong stablt of Sngl-Dagonall-Implct Runge-Kutta methods. Report no MI 007-, 007, Mathematcal Insttute, Leden Unverst. [] Zngg D.W., Chsholm T.T. Runge- Kutta methods for lnear ordnar dfferental equatons, Appled Numercal Mathematcs., 999, pp ISSN: Issue 8, Volume 8, August 009
Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION
Malasa Joural of Mathematcal Sceces (): 95-05 (00) Fourth Order Four-Stage Dagoall Implct Ruge-Kutta Method for Lear Ordar Dfferetal Equatos Nur Izzat Che Jawas, Fudzah Ismal, Mohamed Sulema, 3 Azm Jaafar
More informationOne-sided finite-difference approximations suitable for use with Richardson extrapolation
Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,
More informationNew Method for Solving Poisson Equation. on Irregular Domains
Appled Mathematcal Scences Vol. 6 01 no. 8 369 380 New Method for Solvng Posson Equaton on Irregular Domans J. Izadan and N. Karamooz Department of Mathematcs Facult of Scences Mashhad BranchIslamc Azad
More informationA new Approach for Solving Linear Ordinary Differential Equations
, ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of
More informationNumerical Solution of Ordinary Differential Equations
Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples
More informationNumerical Solutions of a Generalized Nth Order Boundary Value Problems Using Power Series Approximation Method
Appled Mathematcs, 6, 7, 5-4 Publshed Onlne Jul 6 n ScRes. http://www.scrp.org/journal/am http://.do.org/.436/am.6.77 umercal Solutons of a Generalzed th Order Boundar Value Problems Usng Power Seres Approxmaton
More informationE91: Dynamics. E91: Dynamics. Numerical Integration & State Space Representation
E91: Dnamcs Numercal Integraton & State Space Representaton The Algorthm In steps of Δ f ( new ) f ( old ) df ( d old ) Δ Numercal Integraton of ODEs d d f() h Δ Intal value problem: Gven the ntal state
More informationNON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS
IJRRAS 8 (3 September 011 www.arpapress.com/volumes/vol8issue3/ijrras_8_3_08.pdf NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS H.O. Bakodah Dept. of Mathematc
More informationAppendix B. The Finite Difference Scheme
140 APPENDIXES Appendx B. The Fnte Dfference Scheme In ths appendx we present numercal technques whch are used to approxmate solutons of system 3.1 3.3. A comprehensve treatment of theoretcal and mplementaton
More informationCOMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
More informationLecture 21: Numerical methods for pricing American type derivatives
Lecture 21: Numercal methods for prcng Amercan type dervatves Xaoguang Wang STAT 598W Aprl 10th, 2014 (STAT 598W) Lecture 21 1 / 26 Outlne 1 Fnte Dfference Method Explct Method Penalty Method (STAT 598W)
More informationCHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE
CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng
More informationLecture 2: Numerical Methods for Differentiations and Integrations
Numercal Smulaton of Space Plasmas (I [AP-4036] Lecture 2 by Lng-Hsao Lyu March, 2018 Lecture 2: Numercal Methods for Dfferentatons and Integratons As we have dscussed n Lecture 1 that numercal smulaton
More informationPART 8. Partial Differential Equations PDEs
he Islamc Unverst of Gaza Facult of Engneerng Cvl Engneerng Department Numercal Analss ECIV 3306 PAR 8 Partal Dfferental Equatons PDEs Chapter 9; Fnte Dfference: Ellptc Equatons Assocate Prof. Mazen Abualtaef
More informationModule 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:
More informationNumerical Methods. ME Mechanical Lab I. Mechanical Engineering ME Lab I
5 9 Mechancal Engneerng -.30 ME Lab I ME.30 Mechancal Lab I Numercal Methods Volt Sne Seres.5 0.5 SIN(X) 0 3 7 5 9 33 37 4 45 49 53 57 6 65 69 73 77 8 85 89 93 97 0-0.5 Normalzed Squared Functon - 0.07
More informationA Hybrid Variational Iteration Method for Blasius Equation
Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method
More information2 Finite difference basics
Numersche Methoden 1, WS 11/12 B.J.P. Kaus 2 Fnte dfference bascs Consder the one- The bascs of the fnte dfference method are best understood wth an example. dmensonal transent heat conducton equaton T
More informationNUMERICAL DIFFERENTIATION
NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the
More informationChapter 12. Ordinary Differential Equation Boundary Value (BV) Problems
Chapter. Ordnar Dfferental Equaton Boundar Value (BV) Problems In ths chapter we wll learn how to solve ODE boundar value problem. BV ODE s usuall gven wth x beng the ndependent space varable. p( x) q(
More informationChapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems
Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons
More informationLecture 12: Discrete Laplacian
Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly
More informationDETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM
Ganj, Z. Z., et al.: Determnaton of Temperature Dstrbuton for S111 DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM by Davood Domr GANJI
More informationA New Refinement of Jacobi Method for Solution of Linear System Equations AX=b
Int J Contemp Math Scences, Vol 3, 28, no 17, 819-827 A New Refnement of Jacob Method for Soluton of Lnear System Equatons AX=b F Naem Dafchah Department of Mathematcs, Faculty of Scences Unversty of Gulan,
More informationConvexity preserving interpolation by splines of arbitrary degree
Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete
More informationNumerical Heat and Mass Transfer
Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and
More informationConsistency & Convergence
/9/007 CHE 374 Computatonal Methods n Engneerng Ordnary Dfferental Equatons Consstency, Convergence, Stablty, Stffness and Adaptve and Implct Methods ODE s n MATLAB, etc Consstency & Convergence Consstency
More informationExponential Type Product Estimator for Finite Population Mean with Information on Auxiliary Attribute
Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 193-9466 Vol. 10, Issue 1 (June 015), pp. 106-113 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) Exponental Tpe Product Estmator
More informationAdditional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty
Addtonal Codes usng Fnte Dfference Method Benamn Moll 1 HJB Equaton for Consumpton-Savng Problem Wthout Uncertanty Before consderng the case wth stochastc ncome n http://www.prnceton.edu/~moll/ HACTproect/HACT_Numercal_Appendx.pdf,
More informationNumerical Simulation of One-Dimensional Wave Equation by Non-Polynomial Quintic Spline
IOSR Journal of Matematcs (IOSR-JM) e-issn: 78-578, p-issn: 319-765X. Volume 14, Issue 6 Ver. I (Nov - Dec 018), PP 6-30 www.osrournals.org Numercal Smulaton of One-Dmensonal Wave Equaton by Non-Polynomal
More informationLecture 13 APPROXIMATION OF SECOMD ORDER DERIVATIVES
COMPUTATIONAL FLUID DYNAMICS: FDM: Appromaton of Second Order Dervatves Lecture APPROXIMATION OF SECOMD ORDER DERIVATIVES. APPROXIMATION OF SECOND ORDER DERIVATIVES Second order dervatves appear n dffusve
More informationLinear Approximation with Regularization and Moving Least Squares
Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...
More informationME 501A Seminar in Engineering Analysis Page 1
umercal Solutons of oundary-value Problems n Os ovember 7, 7 umercal Solutons of oundary- Value Problems n Os Larry aretto Mechancal ngneerng 5 Semnar n ngneerng nalyss ovember 7, 7 Outlne Revew stff equaton
More informationA NUMERICAL COMPARISON OF LANGRANGE AND KANE S METHODS OF AN ARM SEGMENT
Internatonal Conference Mathematcal and Computatonal ology 0 Internatonal Journal of Modern Physcs: Conference Seres Vol. 9 0 68 75 World Scentfc Publshng Company DOI: 0.4/S009450059 A NUMERICAL COMPARISON
More informationCHAPTER 4 MAX-MIN AVERAGE COMPOSITION METHOD FOR DECISION MAKING USING INTUITIONISTIC FUZZY SETS
56 CHAPER 4 MAX-MIN AVERAGE COMPOSIION MEHOD FOR DECISION MAKING USING INUIIONISIC FUZZY SES 4.1 INRODUCION Intutonstc fuzz max-mn average composton method s proposed to construct the decson makng for
More informationHaar wavelet collocation method to solve problems arising in induction motor
ISSN 746-7659, England, UK Journal of Informaton and Computng Scence Vol., No., 07, pp.096-06 Haar wavelet collocaton method to solve problems arsng n nducton motor A. Padmanabha Reddy *, C. Sateesha,
More informationAPPENDIX A Some Linear Algebra
APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,
More informationThe Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method
Journal of Electromagnetc Analyss and Applcatons, 04, 6, 0-08 Publshed Onlne September 04 n ScRes. http://www.scrp.org/journal/jemaa http://dx.do.org/0.46/jemaa.04.6000 The Exact Formulaton of the Inverse
More information2.29 Numerical Fluid Mechanics Fall 2011 Lecture 12
REVIEW Lecture 11: 2.29 Numercal Flud Mechancs Fall 2011 Lecture 12 End of (Lnear) Algebrac Systems Gradent Methods Krylov Subspace Methods Precondtonng of Ax=b FINITE DIFFERENCES Classfcaton of Partal
More informationLecture 10 Support Vector Machines II
Lecture 10 Support Vector Machnes II 22 February 2016 Taylor B. Arnold Yale Statstcs STAT 365/665 1/28 Notes: Problem 3 s posted and due ths upcomng Frday There was an early bug n the fake-test data; fxed
More informationEEE 241: Linear Systems
EEE : Lnear Systems Summary #: Backpropagaton BACKPROPAGATION The perceptron rule as well as the Wdrow Hoff learnng were desgned to tran sngle layer networks. They suffer from the same dsadvantage: they
More informationCubic Trigonometric B-Spline Applied to Linear Two-Point Boundary Value Problems of Order Two
World Academy of Scence Engneerng and echnology Internatonal Journal of Mathematcal and omputatonal Scences Vol: No:0 00 ubc rgonometrc B-Splne Appled to Lnear wo-pont Boundary Value Problems of Order
More informationNumerical Simulation of Wave Propagation Using the Shallow Water Equations
umercal Smulaton of Wave Propagaton Usng the Shallow Water Equatons Junbo Par Harve udd College 6th Aprl 007 Abstract The shallow water equatons SWE were used to model water wave propagaton n one dmenson
More informationReport on Image warping
Report on Image warpng Xuan Ne, Dec. 20, 2004 Ths document summarzed the algorthms of our mage warpng soluton for further study, and there s a detaled descrpton about the mplementaton of these algorthms.
More informationn α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0
MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector
More informationMD. LUTFOR RAHMAN 1 AND KALIPADA SEN 2 Abstract
ISSN 058-71 Bangladesh J. Agrl. Res. 34(3) : 395-401, September 009 PROBLEMS OF USUAL EIGHTED ANALYSIS OF VARIANCE (ANOVA) IN RANDOMIZED BLOCK DESIGN (RBD) ITH MORE THAN ONE OBSERVATIONS PER CELL HEN ERROR
More informationA MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS
Journal of Mathematcs and Statstcs 9 (1): 4-8, 1 ISSN 1549-644 1 Scence Publcatons do:1.844/jmssp.1.4.8 Publshed Onlne 9 (1) 1 (http://www.thescpub.com/jmss.toc) A MODIFIED METHOD FOR SOLVING SYSTEM OF
More informationThe Finite Element Method
The Fnte Element Method GENERAL INTRODUCTION Read: Chapters 1 and 2 CONTENTS Engneerng and analyss Smulaton of a physcal process Examples mathematcal model development Approxmate solutons and methods of
More informationChapter 4 The Wave Equation
Chapter 4 The Wave Equaton Another classcal example of a hyperbolc PDE s a wave equaton. The wave equaton s a second-order lnear hyperbolc PDE that descrbes the propagaton of a varety of waves, such as
More informationORDINARY DIFFERENTIAL EQUATIONS EULER S METHOD
Numercal Analss or Engneers German Jordanan Unverst ORDINARY DIFFERENTIAL EQUATIONS We wll eplore several metods o solvng rst order ordnar derental equatons (ODEs and we wll sow ow tese metods can be appled
More informationSupplementary Notes for Chapter 9 Mixture Thermodynamics
Supplementary Notes for Chapter 9 Mxture Thermodynamcs Key ponts Nne major topcs of Chapter 9 are revewed below: 1. Notaton and operatonal equatons for mxtures 2. PVTN EOSs for mxtures 3. General effects
More informationDUE: WEDS FEB 21ST 2018
HOMEWORK # 1: FINITE DIFFERENCES IN ONE DIMENSION DUE: WEDS FEB 21ST 2018 1. Theory Beam bendng s a classcal engneerng analyss. The tradtonal soluton technque makes smplfyng assumptons such as a constant
More information4DVAR, according to the name, is a four-dimensional variational method.
4D-Varatonal Data Assmlaton (4D-Var) 4DVAR, accordng to the name, s a four-dmensonal varatonal method. 4D-Var s actually a drect generalzaton of 3D-Var to handle observatons that are dstrbuted n tme. The
More informationResearch Article An Optimized Runge-Kutta Method for the Numerical Solution of the Radial Schrödinger Equation
Mathematcal Problems n Engneerng Volume 212, Artcle ID 867948, 12 pages do:1.1155/212/867948 Research Artcle An Optmzed Runge-Kutta Method for the Numercal Soluton of the Radal Schrödnger Equaton Qnghe
More informationarxiv: v1 [math.co] 12 Sep 2014
arxv:1409.3707v1 [math.co] 12 Sep 2014 On the bnomal sums of Horadam sequence Nazmye Ylmaz and Necat Taskara Department of Mathematcs, Scence Faculty, Selcuk Unversty, 42075, Campus, Konya, Turkey March
More informationSolving Fractional Nonlinear Fredholm Integro-differential Equations via Hybrid of Rationalized Haar Functions
ISSN 746-7659 England UK Journal of Informaton and Computng Scence Vol. 9 No. 3 4 pp. 69-8 Solvng Fractonal Nonlnear Fredholm Integro-dfferental Equatons va Hybrd of Ratonalzed Haar Functons Yadollah Ordokhan
More informationHigh resolution entropy stable scheme for shallow water equations
Internatonal Symposum on Computers & Informatcs (ISCI 05) Hgh resoluton entropy stable scheme for shallow water equatons Xaohan Cheng,a, Yufeng Ne,b, Department of Appled Mathematcs, Northwestern Polytechncal
More informationA Functionally Fitted 3-stage ESDIRK Method Kazufumi Ozawa Akita Prefectural University Honjo Akita , Japan
A Functonally Ftted 3-stage ESDIRK Method Kazufum Ozawa Akta Prefectural Unversty Hono Akta 05-0055, Japan ozawa@akta-pu.ac.p Abstract A specal class of Runge-Kutta (-Nyström) methods called functonally
More informationThe Study of Teaching-learning-based Optimization Algorithm
Advanced Scence and Technology Letters Vol. (AST 06), pp.05- http://dx.do.org/0.57/astl.06. The Study of Teachng-learnng-based Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute
More informationGeneral viscosity iterative method for a sequence of quasi-nonexpansive mappings
Avalable onlne at www.tjnsa.com J. Nonlnear Sc. Appl. 9 (2016), 5672 5682 Research Artcle General vscosty teratve method for a sequence of quas-nonexpansve mappngs Cuje Zhang, Ynan Wang College of Scence,
More informationFUZZY GOAL PROGRAMMING VS ORDINARY FUZZY PROGRAMMING APPROACH FOR MULTI OBJECTIVE PROGRAMMING PROBLEM
Internatonal Conference on Ceramcs, Bkaner, Inda Internatonal Journal of Modern Physcs: Conference Seres Vol. 22 (2013) 757 761 World Scentfc Publshng Company DOI: 10.1142/S2010194513010982 FUZZY GOAL
More informationSuppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl
RECURSIVE SPLINE INTERPOLATION METHOD FOR REAL TIME ENGINE CONTROL APPLICATIONS A. Stotsky Volvo Car Corporaton Engne Desgn and Development Dept. 97542, HA1N, SE- 405 31 Gothenburg Sweden. Emal: astotsky@volvocars.com
More informationCHAPTER-5 INFORMATION MEASURE OF FUZZY MATRIX AND FUZZY BINARY RELATION
CAPTER- INFORMATION MEASURE OF FUZZY MATRI AN FUZZY BINARY RELATION Introducton The basc concept of the fuzz matr theor s ver smple and can be appled to socal and natural stuatons A branch of fuzz matr
More informationA PROCEDURE FOR SIMULATING THE NONLINEAR CONDUCTION HEAT TRANSFER IN A BODY WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY.
Proceedngs of the th Brazlan Congress of Thermal Scences and Engneerng -- ENCIT 006 Braz. Soc. of Mechancal Scences and Engneerng -- ABCM, Curtba, Brazl,- Dec. 5-8, 006 A PROCEDURE FOR SIMULATING THE NONLINEAR
More informationModule 9. Lecture 6. Duality in Assignment Problems
Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept
More informationResearch Article Cubic B-Spline Collocation Method for One-Dimensional Heat and Advection-Diffusion Equations
Appled Mathematcs Volume 22, Artcle ID 4587, 8 pages do:.55/22/4587 Research Artcle Cubc B-Splne Collocaton Method for One-Dmensonal Heat and Advecton-Dffuson Equatons Joan Goh, Ahmad Abd. Majd, and Ahmad
More informationRockefeller College University at Albany
Rockefeller College Unverst at Alban PAD 705 Handout: Maxmum Lkelhood Estmaton Orgnal b Davd A. Wse John F. Kenned School of Government, Harvard Unverst Modfcatons b R. Karl Rethemeer Up to ths pont n
More informationThe Second Anti-Mathima on Game Theory
The Second Ant-Mathma on Game Theory Ath. Kehagas December 1 2006 1 Introducton In ths note we wll examne the noton of game equlbrum for three types of games 1. 2-player 2-acton zero-sum games 2. 2-player
More informationWeek3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity
Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle
More informationDigital Signal Processing
Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over
More informationpage 2 2 dscretzaton mantans ths stablty under a sutable restrcton on the tme step. SSP tme dscretzaton methods were frst developed by Shu n [20] and
page 1 A Survey of Strong Stablty Preservng Hgh Order Tme Dscretzatons Ch-Wang Shu Λ 1 Introducton Numercal soluton for ordnary dfferental equatons (ODEs) s an establshed research area. There are many
More informationarxiv: v1 [math.ho] 18 May 2008
Recurrence Formulas for Fbonacc Sums Adlson J. V. Brandão, João L. Martns 2 arxv:0805.2707v [math.ho] 8 May 2008 Abstract. In ths artcle we present a new recurrence formula for a fnte sum nvolvng the Fbonacc
More informationComparison Solutions Between Lie Group Method and Numerical Solution of (RK4) for Riccati Differential Equation
Appled and Computatonal Mathematcs 06; 5(: 64-7 http://www.scencepublshnggroup.com/j/acm do: 0.648/j.acm.06050.5 ISSN: 8-5605 (Prnt; ISSN: 8-56 (Onlne Comparson Solutons Between Le Group Method and Numercal
More informationIrregular vibrations in multi-mass discrete-continuous systems torsionally deformed
(2) 4 48 Irregular vbratons n mult-mass dscrete-contnuous systems torsonally deformed Abstract In the paper rregular vbratons of dscrete-contnuous systems consstng of an arbtrary number rgd bodes connected
More informationTransfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system
Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng
More informationApplication of B-Spline to Numerical Solution of a System of Singularly Perturbed Problems
Mathematca Aeterna, Vol. 1, 011, no. 06, 405 415 Applcaton of B-Splne to Numercal Soluton of a System of Sngularly Perturbed Problems Yogesh Gupta Department of Mathematcs Unted College of Engneerng &
More informationSingular Value Decomposition: Theory and Applications
Sngular Value Decomposton: Theory and Applcatons Danel Khashab Sprng 2015 Last Update: March 2, 2015 1 Introducton A = UDV where columns of U and V are orthonormal and matrx D s dagonal wth postve real
More informationBallot Paths Avoiding Depth Zero Patterns
Ballot Paths Avodng Depth Zero Patterns Henrch Nederhausen and Shaun Sullvan Florda Atlantc Unversty, Boca Raton, Florda nederha@fauedu, ssull21@fauedu 1 Introducton In a paper by Sapounaks, Tasoulas,
More information2.29 Numerical Fluid Mechanics
REVIEW Lecture 10: Sprng 2015 Lecture 11 Classfcaton of Partal Dfferental Equatons PDEs) and eamples wth fnte dfference dscretzatons Parabolc PDEs Ellptc PDEs Hyperbolc PDEs Error Types and Dscretzaton
More informationWeek 5: Neural Networks
Week 5: Neural Networks Instructor: Sergey Levne Neural Networks Summary In the prevous lecture, we saw how we can construct neural networks by extendng logstc regresson. Neural networks consst of multple
More informationNumerical Solution of One-Dimensional Heat and Wave Equation by Non-Polynomial Quintic Spline
Internatonal Journal of Mathematcal Modellng & Computatons Vol. 05, No. 04, Fall 2015, 291-305 Numercal Soluton of One-Dmensonal Heat and Wave Equaton by Non-Polynomal Quntc Splne J. Rashdna a, and M.
More informationLOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin
Proceedngs of the 007 Wnter Smulaton Conference S G Henderson, B Bller, M-H Hseh, J Shortle, J D Tew, and R R Barton, eds LOW BIAS INTEGRATED PATH ESTIMATORS James M Calvn Department of Computer Scence
More informationHandout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system. and write EOM (1) as two first-order Eqs.
Handout # 6 (MEEN 67) Numercal Integraton to Fnd Tme Response of SDOF mechancal system State Space Method The EOM for a lnear system s M X + DX + K X = F() t () t = X = X X = X = V wth ntal condtons, at
More informationSupport Vector Machines. Vibhav Gogate The University of Texas at dallas
Support Vector Machnes Vbhav Gogate he Unversty of exas at dallas What We have Learned So Far? 1. Decson rees. Naïve Bayes 3. Lnear Regresson 4. Logstc Regresson 5. Perceptron 6. Neural networks 7. K-Nearest
More informationInternational Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013) equation. E. M. E. Zayed and S. A.
Internatonal Conference on Advanced Computer Scence and Electroncs Informaton (ICACSEI ) The two varable (G'/G/G) -expanson method for fndng exact travelng wave solutons of the (+) dmensonal nonlnear potental
More informationDifference Equations
Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1
More informationFuzzy approach to solve multi-objective capacitated transportation problem
Internatonal Journal of Bonformatcs Research, ISSN: 0975 087, Volume, Issue, 00, -0-4 Fuzzy aroach to solve mult-objectve caactated transortaton roblem Lohgaonkar M. H. and Bajaj V. H.* * Deartment of
More informationACTM State Calculus Competition Saturday April 30, 2011
ACTM State Calculus Competton Saturday Aprl 30, 2011 ACTM State Calculus Competton Sprng 2011 Page 1 Instructons: For questons 1 through 25, mark the best answer choce on the answer sheet provde Afterward
More informationTHE STURM-LIOUVILLE EIGENVALUE PROBLEM - A NUMERICAL SOLUTION USING THE CONTROL VOLUME METHOD
Journal of Appled Mathematcs and Computatonal Mechancs 06, 5(), 7-36 www.amcm.pcz.pl p-iss 99-9965 DOI: 0.75/jamcm.06..4 e-iss 353-0588 THE STURM-LIOUVILLE EIGEVALUE PROBLEM - A UMERICAL SOLUTIO USIG THE
More informationA boundary element method with analytical integration for deformation of inhomogeneous elastic materials
Journal of Physcs: Conference Seres PAPER OPEN ACCESS A boundary element method wth analytcal ntegraton for deformaton of nhomogeneous elastc materals To cte ths artcle: Moh. Ivan Azs et al 2018 J. Phys.:
More informationA Solution of the Harry-Dym Equation Using Lattice-Boltzmannn and a Solitary Wave Methods
Appled Mathematcal Scences, Vol. 11, 2017, no. 52, 2579-2586 HIKARI Ltd, www.m-hkar.com https://do.org/10.12988/ams.2017.79280 A Soluton of the Harry-Dym Equaton Usng Lattce-Boltzmannn and a Soltary Wave
More informationA Local Variational Problem of Second Order for a Class of Optimal Control Problems with Nonsmooth Objective Function
A Local Varatonal Problem of Second Order for a Class of Optmal Control Problems wth Nonsmooth Objectve Functon Alexander P. Afanasev Insttute for Informaton Transmsson Problems, Russan Academy of Scences,
More informationModeling Convection Diffusion with Exponential Upwinding
Appled Mathematcs, 013, 4, 80-88 http://dx.do.org/10.436/am.013.48a011 Publshed Onlne August 013 (http://www.scrp.org/journal/am) Modelng Convecton Dffuson wth Exponental Upwndng Humberto C. Godnez *,
More informationAn efficient algorithm for multivariate Maclaurin Newton transformation
Annales UMCS Informatca AI VIII, 2 2008) 5 14 DOI: 10.2478/v10065-008-0020-6 An effcent algorthm for multvarate Maclaurn Newton transformaton Joanna Kapusta Insttute of Mathematcs and Computer Scence,
More informationON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION
Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION
More informationSolving Nonlinear Differential Equations by a Neural Network Method
Solvng Nonlnear Dfferental Equatons by a Neural Network Method Luce P. Aarts and Peter Van der Veer Delft Unversty of Technology, Faculty of Cvlengneerng and Geoscences, Secton of Cvlengneerng Informatcs,
More informationLectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix
Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could
More informationSolutions HW #2. minimize. Ax = b. Give the dual problem, and make the implicit equality constraints explicit. Solution.
Solutons HW #2 Dual of general LP. Fnd the dual functon of the LP mnmze subject to c T x Gx h Ax = b. Gve the dual problem, and make the mplct equalty constrants explct. Soluton. 1. The Lagrangan s L(x,
More informationMultiple-soliton Solutions for Nonlinear Partial Differential Equations
Journal of Mathematcs Research; Vol. 7 No. ; ISSN 9-979 E-ISSN 9-989 Publshed b Canadan Center of Scence and Educaton Multple-solton Solutons for Nonlnear Partal Dfferental Equatons Yanng Tang & Wean Za
More informationCSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography
CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve
More information