2.29 Numerical Fluid Mechanics Spring 2015 Lecture 12

Size: px
Start display at page:

Download "2.29 Numerical Fluid Mechanics Spring 2015 Lecture 12"

Transcription

1 REVIEW Lctur 11: Numrical Fluid Mchaics Sprig 2015 Lctur 12 Fiit Diffrcs basd Polyomial approximatios Obtai polyomial (i gral u-qually spacd), th diffrtiat as dd Nwto s itrpolatig polyomial formulas Triagular Family of Polyomials (cas of Equidistat Samplig, similar if ot quidistat) Lagrag polyomial (Rformulatio of Nwto s polyomial) 0 0, x x f ( x) L ( x) f ( x ) with L ( x) x x Hrmit Polyomials ad Compact/Pad s Diffrc schms (Us th valus of th fuctio ad its drivativ(s) at ods) Fiit Diffrc: Boudary coditios s Diffrt approx. at ad ar th boudary => impacts global ordr of accuracy ad liar systm to b solvd b m u i m i i x ir x i i p q a u Numrical Fluid Mchaics PFJL Lctur 12, 1

2 Numrical Fluid Mchaics Sprig 2015 Lctur 12 REVIEW Lctur 11: Fiit Diffrc: Boudary coditios Diffrt approx. at ad ar th boudary => impacts liar systm to b solvd Fiit-Diffrcs o No-Uiform Grids ad Uiform Errors: 1-D If o-uiform grid is rfid, rror du to th 1 st ordr trm dcrass fastr tha that of 2 d ordr trm Covrgc bcoms asymptotically 2 d ordr (1 st ordr trm cacls) Grid-Rfimt ad Error stimatio Estimatio of th ordr of covrgc ad of th discrtizatio rror Richardso s xtrapolatio ad Itrativ improvmts usig Roombrg s algorithm Numrical Fluid Mchaics PFJL Lctur 12, 2

3 FINITE DIFFERENCES Outli for Today Fiit-Diffrcs o No-Uiform Grids ad Uiform Errors: 1-D Grid Rfimt ad Error Estimatio Fourir Aalysis ad Error Aalysis Diffrtiatio, dfiitio ad smoothss of solutio for ordr of spatial oprators Stability Huristic Mthod Ergy Mthod Vo Numa Mthod (Itroductio) : 1st ordr liar covctio/wav q. Hyprbolic PDEs ad Stability Exampl: 2d ordr wav quatio ad wavs o a strig Effctiv umrical wav umbrs ad disprsio CFL coditio: Dfiitio Exampls: 1st ordr liar covctio/wav q., 2d ordr wav q., othr FD schms Vo Numa xampls: 1st ordr liar covctio/wav q. Tabls of schms for 1st ordr liar covctio/wav q. Numrical Fluid Mchaics PFJL Lctur 12, 3

4 Rfrcs ad Radig Assigmts Lapidus ad Pidr, 1982: Numrical solutios of PDEs i Scic ad Egirig. Sctio 4.5 o Stability. Chaptr 3 o Fiit Diffrc Mthods of J. H. Frzigr ad M. Pric, Computatioal Mthods for Fluid Dyamics. Sprigr, NY, 3 rd ditio, 2002 Chaptr 3 o Fiit Diffrc Approximatios of H. Lomax, T. H. Pulliam, D.W. Zigg, Fudamtals of Computatioal Fluid Dyamics (Scitific Computatio). Sprigr, 2003 Chaptr 29 ad 30 o Fiit Diffrc: Elliptic ad Parabolic quatios of Chapra ad Caal, Numrical Mthods for Egirs, 2014/2010/2006. Numrical Fluid Mchaics PFJL Lctur 12, 4

5 Grid-Rfimt ad Error stimatio W foud that for a covrgt schm, th discrtizatio rror ε is of th form: p (rcall: ˆ, ( ) 0, ˆ ( ˆ ) 0 ) O( x ) R whr R is th rmaidr Th dgr of accuracy ad discrtizatio rror ca b stimatd btw solutios obtaid o systmatically rfid/coarsd grids p uu x x R -Tru solutio u ca b xprssd ithr as: p uu x R -Thus, th xpot p ca b stimatd: 2 ' (2 ) ' (d to limiat u ad th d 2 qs. to limiat both Δx ad p, hc u 4Δx ) -Th discrtizatio rror o th grid Δx ca b stimatd by: -Good ida: stimat p to chc cod. Is it qual to what it is supposd to b? -Wh solutios o svral grids ar availabl, a approximatio of highr accuracy ca b obtaid from th rmaidr: Richardso Extrapolatio! Numrical Fluid Mchaics PFJL Lctur 12, 5 x u u p 2x 4x log log 2 u x u2 x x x x ) u u 2 1 x 2x x p

6 Richardso Extrapolatio ad Rombrg Itgratio Richardso Extrapolatio: mthod to obtai a third improvd stimat of a itgral basd o two othr stimats Cosidr: I(h) For two diffrt grid spac h1 ad h2: Trapzoidal Rul: I 2 Exampl h 2 h 1 h (grid spac) 2 Assum: ) Richardso Extrapolatio: 2 From two O(h 2 ), w gt a O(h 4 )! Numrical Fluid Mchaics PFJL Lctur 12, 6

7 Rombrg s Itgratio: Itrativ applicatio of Richardso s xtrapolatio I(h) Rombrg Itgratio Algorithm, for ay ordr For Ordr 2 (cas of prvious slid): I h 2 h 1 h 1: O(h 2 ) 2: O(h 4 ) 3: O(h 6 ) 4: O(h 8 ) a b, Icrasig ordr c Icrasig rsolutio Numrical Fluid Mchaics PFJL Lctur 12, 7

8 Rombrg s Diffrtiatio: Itrativ applicatio of Richardso s xtrapolatio D(h) Rombrg Diffrtiatio Algorithm, for ay ordr D D D For Ordr 2 (as prvious slid, but for diffrtiatio): D h 3 h 2 h 1 D h 4D 2,1 D 1,1 Icrasig ordr 1: O(h 2 ) 2: O(h 4 ) 3: O(h 6 ) 4: O(h 8 ) a b, c Icrasig rsolutio Numrical Fluid Mchaics PFJL Lctur 12, 8

9 Fourir (Error) Aalysis: Dfiitios Ladig rror trms ad discrtizatio rror stimats ca b complmtd by a Fourir rror aalysis Fourir dcompositio: Ay arbitrary priodic fuctio ca b dcomposd ito its Fourir compots: ix f ( x) f ( itgr, wavumbr) Usig th orthog. proprty, taig th itgral/ft of f(x): 2 0 i x im x Not: rat at which f with dcays dtrmi smoothss of f (x) 2 1 i x f f ( x) dx (orthogoality proprty) Exampls draw i lctur: si(x), Gaussia xp(-πx 2 ), multi-frqucy fuctios, tc m Numrical Fluid Mchaics PFJL Lctur 12, 9

10 Fourir (Error) Aalysis: Diffrtiatios Cosidr th dcompositios: ix f ( x) f or f ( x, t) f ( t) ix Taig spatial drivativs givs: f x f () t i ix Taig tmporal drivativs givs: r r f d f () t r r t dt ix Hc, i particular, for v or odd spatial drivativs: q 2q 2 ( 1) (ral) q i q 2q ( 1) (imagiary) q i i Numrical Fluid Mchaics PFJL Lctur 12, 10

11 Fourir (Error) Aalysis: Gric quatio Cosidr th gric PDE: f t f x Fourir Aalysis: f ( x, t) f ( t) ix Hc: d f () t dt ix f () t i ix Thus: Ad: d f () t dt i f ( t) f ( t) for i t ixt f ( t) f (0), f ( x, t) f(0) Phas spd : c / i Numrical Fluid Mchaics PFJL Lctur 12, 11

12 Fourir (Error) Aalysis: Gric quatio Gric PDE, FT: Hc: Etc ( x, t) f (0) ixt d f () t dt f f Propagatio: c / i 1, 1 i t x No disprsio f f t x Dcay 2 3 f f 3 i 3 t x f ( t) for i 3 2 Propagatio: /, With disprsio f f t x c i : (Fast) Growth, : (Fast) Dcay 4 q 2q 2 ( 1) (ral) q i q 2q ( 1) (imagiary) q i i Numrical Fluid Mchaics PFJL Lctur 12, 12

13 Fourir Error Aalysis: 1 st drivativs f x I th dcompositio: f ( x, t) f ( t) ix All compots ar of th form: Exact 1 st ordr spatial drivativ: Howvr, if w apply th ctrd fiit-diffrc (2 d ordr accurat): f x 1 1 2x ff = ffctiv wavumbr () t ix 3 2 si( x ) ff x... x 6 Shows th 2 d ordr atur of ctr-diffrc approx. (hr, of by ff ) For low wavumbrs (smooth fuctios): f f () t x ix ix f ( t) i f ( t) i ix i ( x x) i ( x x) ix ix si( x) ix i i ff x 2x 2x x f f si( x) whr ff (uiform grid rsolutio x) x ix ix ix Numrical Fluid Mchaics PFJL Lctur 12, 13

14 Diffrt approximatios CDS, 2 d ordr: CDS, 4 th ordr: Pad schm, 4 th ordr: Fourir Error Aalysis, Cot d: Effctiv Wav umbrs ff ff x ix hav diffrt ffctiv wavumbrs 3 2 si( x ) x... x 6 si( x) 4 cos( x) 3x 3i si( x) iff 2 cos( x) x max Δx Sprigr. All rights rsrvd. This cott is xcludd from our Crativ Commos lics. For mor iformatio, s Sourc: Lomax, H., T. Pulliam, D. Zigg. Fudamtals of Computatioal Fluid Dyamics. Sprigr, Not that ff is boudd: Numrical Fluid Mchaics 0 ff max x max PFJL Lctur 12, 14

15 Diffrt approximatios Fourir Error Aalysis, Cot d Effctiv Wav Spds Cosidr liar covctio quatios: For th xact solutio: For th umrical sol.: if x ix also lad to diffrt ffctiv wav spds: which w ca solv xactly (our itrst hr is oly rror du to spatial approx.) um f. ( t) f (0) i ff c t umrical ixi ff c t i ( xcff t) (, ) (0) (0) f x t f f cff ff ff (dfiig ff i ff c i cff ) c f t f c x 0 ixt i ( xct) f ( x, t) f(0) f(0) (sic i c) um. ix um. ix d f ix um. um. ( ) ( ) ( ) ff f f t f t c f t c i dt x c ff c ix Oft, c ff / c < 1 => umrical solutio is too slow. Sic, c ff is a fuctio of th ffctiv wavumbr th schm is disprsiv (v though th PDE is ot) Sprigr. All rights rsrvd. This cott is xcludd from our Crativ Commos lics. For mor iformatio, s Sourc: Lomax, H., T. Pulliam, D. Zigg. Fudamtals of Computatioal Fluid Dyamics. Sprigr, Numrical Fluid Mchaics PFJL Lctur 12, 15

16 Evaluatio of th Stability of a FD Schm: Thr mai approachs Rcall: ( ) ˆ ( ˆ ) ˆ ( ) Stability: ˆ 1 Cost. (for liar systms) Huristic stability: Stability is dfid with rfrc to a rror (.g. roud-off) mad i th calculatio, which is dampd (stability) or grows (istability) Huristic Procdur: Try it out Itroduc a isolatd rror ad obsrv how th rror bhavs Rquirs a xhaustiv sarch to sur full stability, hc maily iformatioal approach Ergy Mthod Basic ida: x x x x Fid a quatity, L 2 orm.g. 2 Shows that it rmais boudd for all Lss usd tha Vo Numa mthod, but ca b applid to oliar quatios ad to o-priodic BCs x x Vo Numa mthod (Fourir Aalysis mthod) Numrical Fluid Mchaics PFJL Lctur 12, 16

17 Evaluatio of th Stability of a FD Schm Ergy Mthod Exampl Cosidr agai: c 0 t x 1 c t x A possibl FD formula ( upwid schm for c>0): (t = Δt, x = Δx) which ca b rwritt: 1 c t (1 ) 1 with x t x Drivatio rmovd du to copyright rstrictios. For th rst of this drivatio,plas s quatios 2.18 through 2.22 i Durra, D. Numrical Mthods for Wav Equatios i Gophysical Fluid Dyamics. Sprigr, ISBN: Numrical Fluid Mchaics PFJL Lctur 12, 17

18 Evaluatio of th Stability of a FD Schm Ergy Mthod Exampl Drivatio rmovd du to copyright rstrictios. For th rst of this drivatio, plas s quatios 2.18 through 2.22 i Durra, D. Numrical Mthods for Wav Equatios i Gophysical Fluid Dyamics. Sprigr, ISBN: Numrical Fluid Mchaics PFJL Lctur 12, 18

19 Widly usd procdur Vo Numa Stability Assums iitial rror ca b rprstd as a Fourir Sris ad cosidrs growth or dcay of ths rrors I thortical ss, applis oly to priodic BC problms ad to liar problms Suprpositio of Fourir mods ca th b usd Agai, us, but for th rror: i x ( x, t) ( t) Big itrstd i rror growth/dcay, cosidr oly o mod: i x t i x ( t) whr is i gral complx ad fuctio of : ( ) Strict Stability: Th rror will ot to grow i tim if t 1 i othr words, for t = Δt, th coditio for strict stability ca b writt: t t 1 or for, 1 vo Numa coditio Norm of amplificatio factor ξ smallr or qual to1 Numrical Fluid Mchaics PFJL Lctur 12, 19

20 MIT OpCoursWar Numrical Fluid Mchaics Sprig 2015 For iformatio about citig ths matrials or our Trms of Us, visit:

Discrete Fourier Transform (DFT)

Discrete Fourier Transform (DFT) Discrt Fourir Trasorm DFT Major: All Egirig Majors Authors: Duc guy http://umricalmthods.g.us.du umrical Mthods or STEM udrgraduats 8/3/29 http://umricalmthods.g.us.du Discrt Fourir Trasorm Rcalld th xpotial

More information

1985 AP Calculus BC: Section I

1985 AP Calculus BC: Section I 985 AP Calculus BC: Sctio I 9 Miuts No Calculator Nots: () I this amiatio, l dots th atural logarithm of (that is, logarithm to th bas ). () Ulss othrwis spcifid, th domai of a fuctio f is assumd to b

More information

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.

More information

15/03/1439. Lectures on Signals & systems Engineering

15/03/1439. Lectures on Signals & systems Engineering Lcturs o Sigals & syms Egirig Dsigd ad Prd by Dr. Ayma Elshawy Elsfy Dpt. of Syms & Computr Eg. Al-Azhar Uivrsity Email : aymalshawy@yahoo.com A sigal ca b rprd as a liar combiatio of basic sigals. Th

More information

An Introduction to Asymptotic Expansions

An Introduction to Asymptotic Expansions A Itroductio to Asmptotic Expasios R. Shaar Subramaia Asmptotic xpasios ar usd i aalsis to dscrib th bhavior of a fuctio i a limitig situatio. Wh a fuctio ( x, dpds o a small paramtr, ad th solutio of

More information

Lectures 9 IIR Systems: First Order System

Lectures 9 IIR Systems: First Order System EE3054 Sigals ad Systms Lcturs 9 IIR Systms: First Ordr Systm Yao Wag Polytchic Uivrsity Som slids icludd ar xtractd from lctur prstatios prpard by McCllla ad Schafr Lics Ifo for SPFirst Slids This work

More information

DTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1

DTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1 DTFT Proprtis Exampl - Dtrmi th DTFT Y of y α µ, α < Lt x α µ, α < W ca thrfor writ y x x From Tabl 3., th DTFT of x is giv by ω X ω α ω Copyright, S. K. Mitra Copyright, S. K. Mitra DTFT Proprtis DTFT

More information

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges.

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges. Optio Chaptr Ercis. Covrgs to Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Divrgs 8 Divrgs Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Covrgs to Covrgs to 8 Proof Covrgs to π l 8 l a b Divrgt π Divrgt

More information

MONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx

MONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx MONTGOMERY COLLEGE Dpartmt of Mathmatics Rockvill Campus MATH 8 - REVIEW PROBLEMS. Stat whthr ach of th followig ca b itgratd by partial fractios (PF), itgratio by parts (PI), u-substitutio (U), or o of

More information

PURE MATHEMATICS A-LEVEL PAPER 1

PURE MATHEMATICS A-LEVEL PAPER 1 -AL P MATH PAPER HONG KONG EXAMINATIONS AUTHORITY HONG KONG ADVANCED LEVEL EXAMINATION PURE MATHEMATICS A-LEVEL PAPER 8 am am ( hours) This papr must b aswrd i Eglish This papr cosists of Sctio A ad Sctio

More information

Review Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2

Review Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2 MATHEMATIS --RE Itgral alculus Marti Huard Witr 9 Rviw Erciss. Evaluat usig th dfiitio of th dfiit itgral as a Rima Sum. Dos th aswr rprst a ara? a ( d b ( d c ( ( d d ( d. Fid f ( usig th Fudamtal Thorm

More information

Chapter 11.00C Physical Problem for Fast Fourier Transform Civil Engineering

Chapter 11.00C Physical Problem for Fast Fourier Transform Civil Engineering haptr. Physical Problm for Fast Fourir Trasform ivil Egirig Itroductio I this chaptr, applicatios of FFT algorithms [-5] for solvig ral-lif problms such as computig th dyamical (displacmt rspos [6-7] of

More information

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series Chatr Ifiit Sris Pag of Sctio F Itgral Tst Chatr : Ifiit Sris By th d of this sctio you will b abl to valuat imror itgrals tst a sris for covrgc by alyig th itgral tst aly th itgral tst to rov th -sris

More information

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z Sris Expasio of Rciprocal of Gamma Fuctio. Fuctios with Itgrs as Roots Fuctio f with gativ itgrs as roots ca b dscribd as follows. f() Howvr, this ifiit product divrgs. That is, such a fuctio caot xist

More information

Chapter Taylor Theorem Revisited

Chapter Taylor Theorem Revisited Captr 0.07 Taylor Torm Rvisitd Atr radig tis captr, you sould b abl to. udrstad t basics o Taylor s torm,. writ trascdtal ad trigoomtric uctios as Taylor s polyomial,. us Taylor s torm to id t valus o

More information

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia Part B: Trasform Mthods Chaptr 3: Discrt-Tim Fourir Trasform (DTFT) 3. Discrt Tim Fourir Trasform (DTFT) 3. Proprtis of DTFT 3.3 Discrt Fourir Trasform (DFT) 3.4 Paddig with Zros ad frqucy Rsolutio 3.5

More information

On the approximation of the constant of Napier

On the approximation of the constant of Napier Stud. Uiv. Babş-Bolyai Math. 560, No., 609 64 O th approximatio of th costat of Napir Adri Vrscu Abstract. Startig from som oldr idas of [] ad [6], w show w facts cocrig th approximatio of th costat of

More information

Statistics 3858 : Likelihood Ratio for Exponential Distribution

Statistics 3858 : Likelihood Ratio for Exponential Distribution Statistics 3858 : Liklihood Ratio for Expotial Distributio I ths two xampl th rjctio rjctio rgio is of th form {x : 2 log (Λ(x)) > c} for a appropriat costat c. For a siz α tst, usig Thorm 9.5A w obtai

More information

Ordinary Differential Equations

Ordinary Differential Equations Basi Nomlatur MAE 0 all 005 Egirig Aalsis Ltur Nots o: Ordiar Diffrtial Equatios Author: Profssor Albrt Y. Tog Tpist: Sakurako Takahashi Cosidr a gral O. D. E. with t as th idpdt variabl, ad th dpdt variabl.

More information

07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n

07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n 07 - SEQUENCES AND SERIES Pag ( Aswrs at h d of all qustios ) ( ) If = a, y = b, z = c, whr a, b, c ar i A.P. ad = 0 = 0 = 0 l a l

More information

Chapter 3 Fourier Series Representation of Periodic Signals

Chapter 3 Fourier Series Representation of Periodic Signals Chptr Fourir Sris Rprsttio of Priodic Sigls If ritrry sigl x(t or x[] is xprssd s lir comitio of som sic sigls th rspos of LI systm coms th sum of th idividul rsposs of thos sic sigls Such sic sigl must:

More information

Session : Plasmas in Equilibrium

Session : Plasmas in Equilibrium Sssio : Plasmas i Equilibrium Ioizatio ad Coductio i a High-prssur Plasma A ormal gas at T < 3000 K is a good lctrical isulator, bcaus thr ar almost o fr lctros i it. For prssurs > 0.1 atm, collisio amog

More information

Introduction to Quantum Information Processing. Overview. A classical randomised algorithm. q 3,3 00 0,0. p 0,0. Lecture 10.

Introduction to Quantum Information Processing. Overview. A classical randomised algorithm. q 3,3 00 0,0. p 0,0. Lecture 10. Itroductio to Quatum Iformatio Procssig Lctur Michl Mosca Ovrviw! Classical Radomizd vs. Quatum Computig! Dutsch-Jozsa ad Brsti- Vazirai algorithms! Th quatum Fourir trasform ad phas stimatio A classical

More information

Numerov-Cooley Method : 1-D Schr. Eq. Last time: Rydberg, Klein, Rees Method and Long-Range Model G(v), B(v) rotation-vibration constants.

Numerov-Cooley Method : 1-D Schr. Eq. Last time: Rydberg, Klein, Rees Method and Long-Range Model G(v), B(v) rotation-vibration constants. Numrov-Cooly Mthod : 1-D Schr. Eq. Last tim: Rydbrg, Kli, Rs Mthod ad Log-Rag Modl G(v), B(v) rotatio-vibratio costats 9-1 V J (x) pottial rgy curv x = R R Ev,J, v,j, all cocivabl xprimts wp( x, t) = ai

More information

Digital Signal Processing, Fall 2006

Digital Signal Processing, Fall 2006 Digital Sigal Procssig, Fall 6 Lctur 9: Th Discrt Fourir Trasfor Zhg-Hua Ta Dpartt of Elctroic Systs Aalborg Uivrsity, Dar zt@o.aau.d Digital Sigal Procssig, I, Zhg-Hua Ta, 6 Cours at a glac MM Discrt-ti

More information

A Simple Proof that e is Irrational

A Simple Proof that e is Irrational Two of th most bautiful ad sigificat umbrs i mathmatics ar π ad. π (approximatly qual to 3.459) rprsts th ratio of th circumfrc of a circl to its diamtr. (approximatly qual to.788) is th bas of th atural

More information

Discrete Fourier Transform. Nuno Vasconcelos UCSD

Discrete Fourier Transform. Nuno Vasconcelos UCSD Discrt Fourir Trasform uo Vascoclos UCSD Liar Shift Ivariat (LSI) systms o of th most importat cocpts i liar systms thory is that of a LSI systm Dfiitio: a systm T that maps [ ito y[ is LSI if ad oly if

More information

Triple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling

Triple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling Tripl Play: From D Morga to Stirlig To Eulr to Maclauri to Stirlig Augustus D Morga (186-1871) was a sigificat Victoria Mathmaticia who mad cotributios to Mathmatics History, Mathmatical Rcratios, Mathmatical

More information

An Introduction to Asymptotic Expansions

An Introduction to Asymptotic Expansions A Itroductio to Asmptotic Expasios R. Shaar Subramaia Dpartmt o Chmical ad Biomolcular Egirig Clarso Uivrsit Asmptotic xpasios ar usd i aalsis to dscrib th bhavior o a uctio i a limitig situatio. Wh a

More information

CDS 101: Lecture 5.1 Reachability and State Space Feedback

CDS 101: Lecture 5.1 Reachability and State Space Feedback CDS, Lctur 5. CDS : Lctur 5. Rachability ad Stat Spac Fdback Richard M. Murray ad Hido Mabuchi 5 Octobr 4 Goals: Di rachability o a cotrol systm Giv tsts or rachability o liar systms ad apply to ampls

More information

to the SCHRODINGER EQUATION The case of an electron propagating in a crystal lattice

to the SCHRODINGER EQUATION The case of an electron propagating in a crystal lattice Lctur Nots PH 411/511 ECE 598 A. La Rosa INTRODUCTION TO QUANTUM MECHANICS CHAPTER-9 From th HAMILTONIAN EQUATIONS to th SCHRODINGER EQUATION Th cas of a lctro propagatig i a crystal lattic 9.1 Hamiltoia

More information

Ordinary Differential Equations

Ordinary Differential Equations Ordiary Diffrtial Equatio Aftr radig thi chaptr, you hould b abl to:. dfi a ordiary diffrtial quatio,. diffrtiat btw a ordiary ad partial diffrtial quatio, ad. Solv liar ordiary diffrtial quatio with fid

More information

CDS 101: Lecture 5.1 Reachability and State Space Feedback

CDS 101: Lecture 5.1 Reachability and State Space Feedback CDS, Lctur 5. CDS : Lctur 5. Rachability ad Stat Spac Fdback Richard M. Murray 7 Octobr 3 Goals: Di rachability o a cotrol systm Giv tsts or rachability o liar systms ad apply to ampls Dscrib th dsig o

More information

10. Joint Moments and Joint Characteristic Functions

10. Joint Moments and Joint Characteristic Functions 0 Joit Momts ad Joit Charactristic Fctios Followig sctio 6 i this sctio w shall itrodc varios paramtrs to compactly rprst th iformatio cotaid i th joit pdf of two rvs Giv two rvs ad ad a fctio g x y dfi

More information

Calculus & analytic geometry

Calculus & analytic geometry Calculus & aalytic gomtry B Sc MATHEMATICS Admissio owards IV SEMESTER CORE COURSE UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION CALICUT UNIVERSITYPO, MALAPPURAM, KERALA, INDIA 67 65 5 School of Distac

More information

Thomas J. Osler. 1. INTRODUCTION. This paper gives another proof for the remarkable simple

Thomas J. Osler. 1. INTRODUCTION. This paper gives another proof for the remarkable simple 5/24/5 A PROOF OF THE CONTINUED FRACTION EXPANSION OF / Thomas J Oslr INTRODUCTION This ar givs aothr roof for th rmarkabl siml cotiud fractio = 3 5 / Hr is ay ositiv umbr W us th otatio x= [ a; a, a2,

More information

APPENDIX: STATISTICAL TOOLS

APPENDIX: STATISTICAL TOOLS I. Nots o radom samplig Why do you d to sampl radomly? APPENDI: STATISTICAL TOOLS I ordr to masur som valu o a populatio of orgaisms, you usually caot masur all orgaisms, so you sampl a subst of th populatio.

More information

STIRLING'S 1 FORMULA AND ITS APPLICATION

STIRLING'S 1 FORMULA AND ITS APPLICATION MAT-KOL (Baja Luka) XXIV ()(08) 57-64 http://wwwimviblorg/dmbl/dmblhtm DOI: 075/МК80057A ISSN 0354-6969 (o) ISSN 986-588 (o) STIRLING'S FORMULA AND ITS APPLICATION Šfkt Arslaagić Sarajvo B&H Abstract:

More information

Probability & Statistics,

Probability & Statistics, Probability & Statistics, BITS Pilai K K Birla Goa Campus Dr. Jajati Kshari Sahoo Dpartmt of Mathmatics BITS Pilai, K K Birla Goa Campus Poisso Distributio Poisso Distributio: A radom variabl X is said

More information

Chapter 4 - The Fourier Series

Chapter 4 - The Fourier Series M. J. Robrts - 8/8/4 Chaptr 4 - Th Fourir Sris Slctd Solutios (I this solutio maual, th symbol,, is usd for priodic covolutio bcaus th prfrrd symbol which appars i th txt is ot i th fot slctio of th word

More information

EE 232 Lightwave Devices Lecture 3: Basic Semiconductor Physics and Optical Processes. Optical Properties of Semiconductors

EE 232 Lightwave Devices Lecture 3: Basic Semiconductor Physics and Optical Processes. Optical Properties of Semiconductors 3 Lightwav Dvics Lctur 3: Basic Smicoductor Physics ad Optical Procsss Istructor: Mig C. Wu Uivrsity of Califoria, Brly lctrical girig ad Computr Scics Dpt. 3 Lctur 3- Optical Proprtis of Smicoductors

More information

COLLECTION OF SUPPLEMENTARY PROBLEMS CALCULUS II

COLLECTION OF SUPPLEMENTARY PROBLEMS CALCULUS II COLLECTION OF SUPPLEMENTARY PROBLEMS I. CHAPTER 6 --- Trscdtl Fuctios CALCULUS II A. FROM CALCULUS BY J. STEWART:. ( How is th umbr dfid? ( Wht is pproimt vlu for? (c ) Sktch th grph of th turl potil fuctios.

More information

Frequency Measurement in Noise

Frequency Measurement in Noise Frqucy Masurmt i ois Porat Sctio 6.5 /4 Frqucy Mas. i ois Problm Wat to o look at th ct o ois o usig th DFT to masur th rqucy o a siusoid. Cosidr sigl complx siusoid cas: j y +, ssum Complx Whit ois Gaussia,

More information

Ideal crystal : Regulary ordered point masses connected via harmonic springs

Ideal crystal : Regulary ordered point masses connected via harmonic springs Statistical thrmodyamics of crystals Mooatomic crystal Idal crystal : Rgulary ordrd poit masss coctd via harmoic sprigs Itratomic itractios Rprstd by th lattic forc-costat quivalt atom positios miima o

More information

EFFECT OF P-NORMS ON THE ACCURACY ORDER OF NUMERICAL SOLUTION ERRORS IN CFD

EFFECT OF P-NORMS ON THE ACCURACY ORDER OF NUMERICAL SOLUTION ERRORS IN CFD rocdigs of NIT 00 opyright 00 by ABM 3 th Brazilia ogrss of Thrmal Scics ad girig Dcmbr 05-0, 00, brladia, MG, Brazil T O -NORMS ON TH ARAY ORDR O NMRIAL SOLTION RRORS IN D arlos Hriqu Marchi, marchi@ufpr.br

More information

Chapter Five. More Dimensions. is simply the set of all ordered n-tuples of real numbers x = ( x 1

Chapter Five. More Dimensions. is simply the set of all ordered n-tuples of real numbers x = ( x 1 Chatr Fiv Mor Dimsios 51 Th Sac R W ar ow rard to mov o to sacs of dimsio gratr tha thr Ths sacs ar a straightforward gralizatio of our Euclida sac of thr dimsios Lt b a ositiv itgr Th -dimsioal Euclida

More information

SOLUTION OF THE HYPERBOLIC KEPLER EQUATION BY ADOMIAN S ASYMPTOTIC DECOMPOSITION METHOD

SOLUTION OF THE HYPERBOLIC KEPLER EQUATION BY ADOMIAN S ASYMPTOTIC DECOMPOSITION METHOD Romaia Rports i Physics 70, XYZ (08) SOLUTION OF THE HYPERBOLIC KEPLER EQUATION BY ADOMIAN S ASYMPTOTIC DECOMPOSITION METHOD ABDULRAHMAN F ALJOHANI, RANDOLPH RACH, ESSAM EL-ZAHAR,4, ABDUL-MAJID WAZWAZ

More information

Class #24 Monday, April 16, φ φ φ

Class #24 Monday, April 16, φ φ φ lass #4 Moday, April 6, 08 haptr 3: Partial Diffrtial Equatios (PDE s First of all, this sctio is vry, vry difficult. But it s also supr cool. PDE s thr is mor tha o idpdt variabl. Exampl: φ φ φ φ = 0

More information

Higher-Order Discrete Calculus Methods

Higher-Order Discrete Calculus Methods Highr-Ordr Discrt Calculus Mthods J. Blair Prot V. Subramanian Ralistic Practical, Cost-ctiv, Physically Accurat Paralll, Moving Msh, Complx Gomtry, Slid 1 Contxt Discrt Calculus Mthods Finit Dirnc Mimtic

More information

Time : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120

Time : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120 Tim : hr. Tst Papr 8 D 4//5 Bch - R Marks : SINGLE CORRECT CHOICE TYPE [4, ]. If th compl umbr z sisfis th coditio z 3, th th last valu of z is qual to : z (A) 5/3 (B) 8/3 (C) /3 (D) o of ths 5 4. Th itgral,

More information

Discrete Fourier Series and Transforms

Discrete Fourier Series and Transforms Lctur 4 Outi: Discrt Fourir Sris ad Trasforms Aoucmts: H 4 postd, du Tus May 8 at 4:3pm. o at Hs as soutios wi b avaiab immdiaty. Midtrm dtais o t pag H 5 wi b postd Fri May, du foowig Fri (as usua) Rviw

More information

New Sixteenth-Order Derivative-Free Methods for Solving Nonlinear Equations

New Sixteenth-Order Derivative-Free Methods for Solving Nonlinear Equations Amrica Joural o Computatioal ad Applid Mathmatics 0 (: -8 DOI: 0.59/j.ajcam.000.08 Nw Sixtth-Ordr Drivativ-Fr Mthods or Solvig Noliar Equatios R. Thukral Padé Rsarch Ctr 9 Daswood Hill Lds Wst Yorkshir

More information

H2 Mathematics Arithmetic & Geometric Series ( )

H2 Mathematics Arithmetic & Geometric Series ( ) H Mathmatics Arithmtic & Gomtric Sris (08 09) Basic Mastry Qustios Arithmtic Progrssio ad Sris. Th rth trm of a squc is 4r 7. (i) Stat th first four trms ad th 0th trm. (ii) Show that th squc is a arithmtic

More information

Journal of Modern Applied Statistical Methods

Journal of Modern Applied Statistical Methods Joural of Modr Applid Statistical Mthods Volum Issu Articl 6 --03 O Som Proprtis of a Htrogous Trasfr Fuctio Ivolvig Symmtric Saturatd Liar (SATLINS) with Hyprbolic Tagt (TANH) Trasfr Fuctios Christophr

More information

Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform

Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform Discrt Fourir Trasform Dfiitio - T simplst rlatio btw a lt- squc x dfid for ω ad its DTFT X ( ) is ω obtaid by uiformly sampli X ( ) o t ω-axis btw ω < at ω From t dfiitio of t DTFT w tus av X X( ω ) ω

More information

CORRECTIONS TO THE WU-SPRUNG POTENTIAL FOR THE RIEMANN ZEROS AND A NEW HAMILTONIAN WHOSE ENERGIES ARE THE PRIME NUMBERS

CORRECTIONS TO THE WU-SPRUNG POTENTIAL FOR THE RIEMANN ZEROS AND A NEW HAMILTONIAN WHOSE ENERGIES ARE THE PRIME NUMBERS CORRECTIONS TO THE WU-SPRUNG POTENTIAL FOR THE RIEMANN ZEROS AND A NEW HAMILTONIAN WHOSE ENERGIES ARE THE PRIME NUMBERS Jos Javir Garcia Morta Graduat studt of Physics at th UPV/EHU (Uivrsity of Basqu

More information

NET/JRF, GATE, IIT JAM, JEST, TIFR

NET/JRF, GATE, IIT JAM, JEST, TIFR Istitut for NET/JRF, GATE, IIT JAM, JEST, TIFR ad GRE i PHYSICAL SCIENCES Mathmatical Physics JEST-6 Q. Giv th coditio φ, th solutio of th quatio ψ φ φ is giv by k. kφ kφ lφ kφ lφ (a) ψ (b) ψ kφ (c) ψ

More information

Fooling Newton s Method a) Find a formula for the Newton sequence, and verify that it converges to a nonzero of f. A Stirling-like Inequality

Fooling Newton s Method a) Find a formula for the Newton sequence, and verify that it converges to a nonzero of f. A Stirling-like Inequality Foolig Nwto s Mthod a Fid a formla for th Nwto sqc, ad vrify that it covrgs to a ozro of f. ( si si + cos 4 4 3 4 8 8 bt f. b Fid a formla for f ( ad dtrmi its bhavior as. f ( cos si + as A Stirlig-li

More information

International Journal of Advanced and Applied Sciences

International Journal of Advanced and Applied Sciences Itratioal Joural of Advacd ad Applid Scics x(x) xxxx Pags: xx xx Cotts lists availabl at Scic Gat Itratioal Joural of Advacd ad Applid Scics Joural hompag: http://wwwscic gatcom/ijaashtml Symmtric Fuctios

More information

Mixed Mode Oscillations as a Mechanism for Pseudo-Plateau Bursting

Mixed Mode Oscillations as a Mechanism for Pseudo-Plateau Bursting Mixd Mod Oscillatios as a Mchaism for Psudo-Platau Burstig Richard Brtram Dpartmt of Mathmatics Florida Stat Uivrsity Tallahass, FL Collaborators ad Support Thodor Vo Marti Wchslbrgr Joël Tabak Uivrsity

More information

Chapter (8) Estimation and Confedence Intervals Examples

Chapter (8) Estimation and Confedence Intervals Examples Chaptr (8) Estimatio ad Cofdc Itrvals Exampls Typs of stimatio: i. Poit stimatio: Exampl (1): Cosidr th sampl obsrvatios, 17,3,5,1,18,6,16,10 8 X i i1 17 3 5 118 6 16 10 116 X 14.5 8 8 8 14.5 is a poit

More information

Response of LTI Systems to Complex Exponentials

Response of LTI Systems to Complex Exponentials 3 Fourir sris coiuous-im Rspos of LI Sysms o Complx Expoials Ouli Cosidr a LI sysm wih h ui impuls rspos Suppos h ipu sigal is a complx xpoial s x s is a complx umbr, xz zis a complx umbr h or h h w will

More information

A Review of Complex Arithmetic

A Review of Complex Arithmetic /0/005 Rviw of omplx Arithmti.do /9 A Rviw of omplx Arithmti A omplx valu has both a ral ad imagiary ompot: { } ad Im{ } a R b so that w a xprss this omplx valu as: whr. a + b Just as a ral valu a b xprssd

More information

Washington State University

Washington State University he 3 Ktics ad Ractor Dsig Sprg, 00 Washgto Stat Uivrsity Dpartmt of hmical Egrg Richard L. Zollars Exam # You will hav o hour (60 muts) to complt this xam which cosists of four (4) problms. You may us

More information

EC1305 SIGNALS & SYSTEMS

EC1305 SIGNALS & SYSTEMS EC35 SIGNALS & SYSTES DEPT/ YEAR/ SE: IT/ III/ V PREPARED BY: s. S. TENOZI/ Lcturr/ECE SYLLABUS UNIT I CLASSIFICATION OF SIGNALS AND SYSTES Cotiuous Tim Sigals (CT Sigals Discrt Tim Sigals (DT Sigals Stp

More information

ω (argument or phase)

ω (argument or phase) Imagiary uit: i ( i Complx umbr: z x+ i y Cartsia coordiats: x (ral part y (imagiary part Complx cougat: z x i y Absolut valu: r z x + y Polar coordiats: r (absolut valu or modulus ω (argumt or phas x

More information

How many neutrino species?

How many neutrino species? ow may utrio scis? Two mthods for dtrmii it lium abudac i uivrs At a collidr umbr of utrio scis Exasio of th uivrs is ovrd by th Fridma quatio R R 8G tot Kc R Whr: :ubblcostat G :Gravitatioal costat 6.

More information

Fourier Series: main points

Fourier Series: main points BIOEN 3 Lcur 6 Fourir rasforms Novmbr 9, Fourir Sris: mai pois Ifii sum of sis, cosis, or boh + a a cos( + b si( All frqucis ar igr mulipls of a fudamal frqucy, o F.S. ca rprs ay priodic fucio ha w ca

More information

Chapter At each point (x, y) on the curve, y satisfies the condition

Chapter At each point (x, y) on the curve, y satisfies the condition Chaptr 6. At ach poit (, y) o th curv, y satisfis th coditio d y 6; th li y = 5 is tagt to th curv at th poit whr =. I Erciss -6, valuat th itgral ivolvig si ad cosi.. cos si. si 5 cos 5. si cos 5. cos

More information

Solution to 1223 The Evil Warden.

Solution to 1223 The Evil Warden. Solutio to 1 Th Evil Ward. This is o of thos vry rar PoWs (I caot thik of aothr cas) that o o solvd. About 10 of you submittd th basic approach, which givs a probability of 47%. I was shockd wh I foud

More information

Hadamard Exponential Hankel Matrix, Its Eigenvalues and Some Norms

Hadamard Exponential Hankel Matrix, Its Eigenvalues and Some Norms Math Sci Ltt Vol No 8-87 (0) adamard Exotial al Matrix, Its Eigvalus ad Som Norms İ ad M bula Mathmatical Scics Lttrs Itratioal Joural @ 0 NSP Natural Scics Publishig Cor Dartmt of Mathmatics, aculty of

More information

ln x = n e = 20 (nearest integer)

ln x = n e = 20 (nearest integer) H JC Prlim Solutios 6 a + b y a + b / / dy a b 3/ d dy a b at, d Giv quatio of ormal at is y dy ad y wh. d a b () (,) is o th curv a+ b () y.9958 Qustio Solvig () ad (), w hav a, b. Qustio d.77 d d d.77

More information

Computational Fluid Dynamics. Lecture 3

Computational Fluid Dynamics. Lecture 3 Computatioal Fluid Dyamics Lecture 3 Discretizatio Cotiued. A fourth order approximatio to f x ca be foud usig Taylor Series. ( + ) + ( + ) + + ( ) + ( ) = a f x x b f x x c f x d f x x e f x x f x 0 0

More information

COMPUTING FOLRIER AND LAPLACE TRANSFORMS. Sven-Ake Gustafson. be a real-valued func'cion, defined for nonnegative arguments.

COMPUTING FOLRIER AND LAPLACE TRANSFORMS. Sven-Ake Gustafson. be a real-valued func'cion, defined for nonnegative arguments. 77 COMPUTNG FOLRER AND LAPLACE TRANSFORMS BY MEANS OF PmER SERES EVALU\TON Sv-Ak Gustafso 1. NOTATONS AND ASSUMPTONS Lt f b a ral-valud fuc'cio, dfid for ogativ argumts. W shall discuss som aspcts of th

More information

Difference -Analytical Method of The One-Dimensional Convection-Diffusion Equation

Difference -Analytical Method of The One-Dimensional Convection-Diffusion Equation Diffrnc -Analytical Mthod of Th On-Dimnsional Convction-Diffusion Equation Dalabav Umurdin Dpartmnt mathmatic modlling, Univrsity of orld Economy and Diplomacy, Uzbistan Abstract. An analytical diffrncing

More information

ECE594I Notes set 6: Thermal Noise

ECE594I Notes set 6: Thermal Noise C594I ots, M. odwll, copyrightd C594I Nots st 6: Thrmal Nois Mark odwll Uivrsity of Califoria, ata Barbara rodwll@c.ucsb.du 805-893-344, 805-893-36 fax frcs ad Citatios: C594I ots, M. odwll, copyrightd

More information

(1) Then we could wave our hands over this and it would become:

(1) Then we could wave our hands over this and it would become: MAT* K285 Spring 28 Anthony Bnoit 4/17/28 Wk 12: Laplac Tranform Rading: Kohlr & Johnon, Chaptr 5 to p. 35 HW: 5.1: 3, 7, 1*, 19 5.2: 1, 5*, 13*, 19, 45* 5.3: 1, 11*, 19 * Pla writ-up th problm natly and

More information

Taylor and Maclaurin Series

Taylor and Maclaurin Series Taylor ad Maclauri Sris Taylor ad Maclauri Sris Thory sctio which dals with th followig topics: - Th Sigma otatio for summatio. - Dfiitio of Taylor sris. - Commo Maclauri sris. - Taylor sris ad Itrval

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

Narayana IIT Academy

Narayana IIT Academy INDIA Sc: LT-IIT-SPARK Dat: 9--8 6_P Max.Mars: 86 KEY SHEET PHYSIS A 5 D 6 7 A,B 8 B,D 9 A,B A,,D A,B, A,B B, A,B 5 A 6 D 7 8 A HEMISTRY 9 A B D B B 5 A,B,,D 6 A,,D 7 B,,D 8 A,B,,D 9 A,B, A,B, A,B,,D A,B,

More information

Problem Value Score Earned No/Wrong Rec -3 Total

Problem Value Score Earned No/Wrong Rec -3 Total GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING ECE6 Fall Quiz # Writt Eam Novmr, NAME: Solutio Kys GT Usram: LAST FIRST.g., gtiit Rcitatio Sctio: Circl t dat & tim w your Rcitatio

More information

+ x. x 2x. 12. dx. 24. dx + 1)

+ x. x 2x. 12. dx. 24. dx + 1) INTEGRATION of FUNCTION of ONE VARIABLE INDEFINITE INTEGRAL Fidig th idfiit itgrals Rductio to basic itgrals, usig th rul f ( ) f ( ) d =... ( ). ( )d. d. d ( ). d. d. d 7. d 8. d 9. d. d. d. d 9. d 9.

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

Euler s Method for Solving Initial Value Problems in Ordinary Differential Equations.

Euler s Method for Solving Initial Value Problems in Ordinary Differential Equations. Eulr s Mthod for Solvig Iitial Valu Problms i Ordiar Diffrtial Equatios. Suda Fadugba, M.Sc. * ; Bosd Ogurid, Ph.D. ; ad Tao Okulola, M.Sc. 3 Dpartmt of Mathmatical ad Phsical Scics, Af Babalola Uivrsit,

More information

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia Par B: rasform Mhods Profssor E. Ambikairaah UNSW, Ausralia Chapr : Fourir Rprsaio of Sigal. Fourir Sris. Fourir rasform.3 Ivrs Fourir rasform.4 Propris.4. Frqucy Shif.4. im Shif.4.3 Scalig.4.4 Diffriaio

More information

Iterative Methods of Order Four for Solving Nonlinear Equations

Iterative Methods of Order Four for Solving Nonlinear Equations Itrativ Mods of Ordr Four for Solvig Noliar Equatios V.B. Kumar,Vatti, Shouri Domii ad Mouia,V Dpartmt of Egirig Mamatis, Formr Studt of Chmial Egirig Adhra Uivrsity Collg of Egirig A, Adhra Uivrsity Visakhapatam

More information

Restricted Factorial And A Remark On The Reduced Residue Classes

Restricted Factorial And A Remark On The Reduced Residue Classes Applid Mathmatics E-Nots, 162016, 244-250 c ISSN 1607-2510 Availabl fr at mirror sits of http://www.math.thu.du.tw/ am/ Rstrictd Factorial Ad A Rmark O Th Rducd Rsidu Classs Mhdi Hassai Rcivd 26 March

More information

Partition Functions and Ideal Gases

Partition Functions and Ideal Gases Partitio Fuctios ad Idal Gass PFIG- You v lard about partitio fuctios ad som uss ow w ll xplor tm i mor dpt usig idal moatomic diatomic ad polyatomic gass! for w start rmmbr: Q( N ( N! N Wat ar N ad? W

More information

1 Isoparametric Concept

1 Isoparametric Concept UNIVERSITY OF CALIFORNIA BERKELEY Dpartmnt of Civil Enginring Spring 06 Structural Enginring, Mchanics and Matrials Profssor: S. Govindj Nots on D isoparamtric lmnts Isoparamtric Concpt Th isoparamtric

More information

Physics of the Interstellar and Intergalactic Medium

Physics of the Interstellar and Intergalactic Medium PYA0 Sior Sophistr Physics of th Itrstllar ad Itrgalactic Mdium Lctur 7: II gios Dr Graham M. arpr School of Physics, TCD Follow-up radig for this ad t lctur Chaptr 5: Dyso ad Williams (lss dtaild) Chaptr

More information

Scattering Parameters. Scattering Parameters

Scattering Parameters. Scattering Parameters Motivatio cattrig Paramtrs Difficult to implmt op ad short circuit coditios i high frqucis masurmts du to parasitic s ad Cs Pottial stability problms for activ dvics wh masurd i oopratig coditios Difficult

More information

2617 Mark Scheme June 2005 Mark Scheme 2617 June 2005

2617 Mark Scheme June 2005 Mark Scheme 2617 June 2005 Mark Schm 67 Ju 5 GENERAL INSTRUCTIONS Marks i th mark schm ar plicitly dsigatd as M, A, B, E or G. M marks ("mthod" ar for a attmpt to us a corrct mthod (ot mrly for statig th mthod. A marks ("accuracy"

More information

n n ee (for index notation practice, see if you can verify the derivation given in class)

n n ee (for index notation practice, see if you can verify the derivation given in class) EN24: Computatioal mthods i Structural ad Solid Mchaics Homwork 6: Noliar matrials Du Wd Oct 2, 205 School of Egirig Brow Uivrsity I this homwork you will xtd EN24FEA to solv problms for oliar matrials.

More information

2.29 Numerical Fluid Mechanics Spring 2015 Lecture 13

2.29 Numerical Fluid Mechanics Spring 2015 Lecture 13 REVIEW Lecture 12: Spring 2015 Lecture 13 Grid-Refinement and Error estimation Estimation of the order of convergence and of the discretization error Richardson s extrapolation and Iterative improvements

More information

Empirical Study in Finite Correlation Coefficient in Two Phase Estimation

Empirical Study in Finite Correlation Coefficient in Two Phase Estimation M. Khoshvisa Griffith Uivrsity Griffith Busiss School Australia F. Kaymarm Massachustts Istitut of Tchology Dpartmt of Mchaical girig USA H. P. Sigh R. Sigh Vikram Uivrsity Dpartmt of Mathmatics ad Statistics

More information

SOLVED EXAMPLES. Ex.1 If f(x) = , then. is equal to- Ex.5. f(x) equals - (A) 2 (B) 1/2 (C) 0 (D) 1 (A) 1 (B) 2. (D) Does not exist = [2(1 h)+1]= 3

SOLVED EXAMPLES. Ex.1 If f(x) = , then. is equal to- Ex.5. f(x) equals - (A) 2 (B) 1/2 (C) 0 (D) 1 (A) 1 (B) 2. (D) Does not exist = [2(1 h)+1]= 3 SOLVED EXAMPLES E. If f() E.,,, th f() f() h h LHL RHL, so / / Lim f() quls - (D) Dos ot ist [( h)+] [(+h) + ] f(). LHL E. RHL h h h / h / h / h / h / h / h As.[C] (D) Dos ot ist LHL RHL, so giv it dos

More information

Normal Form for Systems with Linear Part N 3(n)

Normal Form for Systems with Linear Part N 3(n) Applid Mathmatics 64-647 http://dxdoiorg/46/am7 Publishd Oli ovmbr (http://wwwscirporg/joural/am) ormal Form or Systms with Liar Part () Grac Gachigua * David Maloza Johaa Sigy Dpartmt o Mathmatics Collg

More information

Figure 2-18 Thevenin Equivalent Circuit of a Noisy Resistor

Figure 2-18 Thevenin Equivalent Circuit of a Noisy Resistor .8 NOISE.8. Th Nyquist Nois Thorm W ow wat to tur our atttio to ois. W will start with th basic dfiitio of ois as usd i radar thory ad th discuss ois figur. Th typ of ois of itrst i radar thory is trmd

More information

Traveling Salesperson Problem and Neural Networks. A Complete Algorithm in Matrix Form

Traveling Salesperson Problem and Neural Networks. A Complete Algorithm in Matrix Form Procdigs of th th WSEAS Itratioal Cofrc o COMPUTERS, Agios Nikolaos, Crt Islad, Grc, July 6-8, 7 47 Travlig Salsprso Problm ad Nural Ntworks A Complt Algorithm i Matrix Form NICOLAE POPOVICIU Faculty of

More information

6. Comparison of NLMS-OCF with Existing Algorithms

6. Comparison of NLMS-OCF with Existing Algorithms 6. Compariso of NLMS-OCF with Eistig Algorithms I Chaptrs 5 w drivd th NLMS-OCF algorithm, aalyzd th covrgc ad trackig bhavior of NLMS-OCF, ad dvlopd a fast vrsio of th NLMS-OCF algorithm. W also mtiod

More information