CHAPTER 4a. ROOTS OF EQUATIONS

Size: px
Start display at page:

Download "CHAPTER 4a. ROOTS OF EQUATIONS"

Transcription

1 CHAPTER 4. ROOTS OF EQUATIONS A. J. Clrk School o Engineering Deprtment o Civil nd Environmentl Engineering by Dr. Ibrhim A. Asskk Spring 00 ENCE 03 - Computtion Methods in Civil Engineering II Deprtment o Civil nd Environmentl Engineering University o Mrylnd, College Prk Introduction Qudrtic Formul In high school, students usully lern how to use the qudrtic ormul b ± x b 4c to solve qudrtic eqution o the type () x x + bx + c 0 () () Slide No.

2 Introduction Qudrtic Formul The vlues clculted with Eq. re clled the roots o Eq.. They represent the vlues o x tht mke Eq. equl to zero. Thus, the root (roots) o n eqution cn be deined s the vlue (vlues) o x tht mkes the eqution equl to zero. Slide No. Introduction Root o Eqution Deinition The root (roots) o n eqution is deined s the vlue (vlues) o x tht mke the eqution () x 0 equl to zero. The roots o n eqution sometimes re clled the zeros o the eqution. Slide No. 3

3 Introduction Anlyticl Solution The roots ( two roots) or qudrtic eqution re sid to be ound nlyticlly. The re ound through the use o the qudrtic ormul. For third-order polynomil, the roots (three roots) cn lso be ound nlyticlly. However, no generl solution exists or other higher-order polynomils. Slide No. 4 Introduction Numericl Solution The solution o mny scientiic nd engineering problems requires inding the roots o equtions tht re complex nd nonliner in nture. For exmple, the unction (x) e -x x cnnot be solved nlyticlly. In such instnces, the only lterntive is n pproximtion by numericl methods. Slide No. 5 3

4 Introduction Numericl Solution To obtin the roots o (x) e -x x 0, some type o itertive numericl method must be employed. This is, in generl, requires lrge number o clcultions, prticulrly, i the roots re to be determined to high degree precision. Thus the problem is well suited to numericl nlysis. Slide No. 6 Introduction Types o Equtions There re typiclly two types o equtions tht relte to roots inding: Algebric Trnscendentl Equtions Polynomils re simple clss o lgebric unctions tht represented generlly by n n () x + x + x +... x + 0 n Slide No. 7 4

5 Introduction Types o Equtions Some speciic exmples o lgebric (polynomils) equtions re nd () x 3.47x + 8.5x 3 6 () x 4x x + 6x Slide No. 8 Introduction Types o Equtions A trnscendentl unction is one tht is non- lgebric. These include trigonometric, exponentil, logrithmic, nd others. Speciic exmples re x () x sin() x 0 nd () x ln( x ) Slide No. 9 5

6 Introduction Roots o Equtions Depending on the type, n eqution cn hve one, two, or more roots. Furthermore, the roots o equtions cn be either rel or complex. Exmple complex roots re x +i nd x -i o the ollowing qudrtic eqution: x x b ± x b 4c ± 4 4()(5) ± () 6 ± i Slide No. 0 Introduction Roots o Equtions No Roots (x) x Slide No. 6

7 Introduction (x) Roots o Equtions One Roots Root x Slide No. Introduction (x) Roots o Equtions Two Roots Roots x Slide No. 3 7

8 Introduction Roots o Equtions Three Roots (x) Roots x Slide No. 4 Introduction Roots o Equtions Although there re situtions where complex roots o nonpolynomils re o interest, such cses re less common thn or polynomils. The stndrd methods or locting roots typiclly ll into two somewht relted but primrily distinct clsses o problems: Slide No. 5 8

9 Introduction Roots o Equtions. The determintion o the rel roots o lgebric nd trnscendentl equtions. These techniques re usully designed to determine the vlue o single rel root on the bsis o its pproximte loction.. The determintion o ll rel nd complex roots o polynomils. These methods re speciiclly designed or polynomils. The systemticlly determine ll roots o the polynomils rther thn determining single rel root given n pproximte loction. Slide No. 6 Eigenvlue Anlysis Engineering Applictions A lrge number o engineering problems require the determintion o set o vlues clled eigenvlues or chrcteristic vlues. The electricl engineer, or exmple, uses eigenvlue nlysis in the solution o twoterminl networks nd in the optimiztion o djustments o control system. Slide No. 7 9

10 Eigenvlue Anlysis Engineering Applictions A structurl engineer uses eigenvlue nlysis in the design o structure to resist ground motion due n erthquke. The chemicl engineer uses eigenvlue nlysis in the design o rector systems. The eronuticl engineer pplies eigenvlue nlyses in nlyzing the lutter o n irplne wing. Slide No. 8 Eigenvlue Anlysis Wht re Egienvlues? Eigenvlues or chrcteristic vlues re vlues, usully denoted s, or which the ollowibg mtrix system hs nonzero (I.e., nontrivil) solution X. [ I ] A n n mtrix A X 0 (3) I n n identity digonl mtrix prmeter clled eigen vlue Slide No. 9 0

11 Eigenvlue Anlysis Eigenvlues Chrcteristic Eqution The chrcteristic equtions o the eigenvlues cn be obtined by expnding the ollowing expression: A I 0 (4) into polynomil, nd then set this polynomil equl to zero. Solving this eqution or the roots s gives the eigenvlues. Slide No. 0 Eigenvlue Anlysis Exmple : 3 3 mtrix: Find the eigenvlues o the ollowing mtrix mtrix: A Slide No.

12 Eigenvlue Anlysis Exmple (cont d): 3 3 mtrix: A I Slide No. Eigenvlue Anlysis or Exmple (cont d): 3 3 mtrix: ( )( [ )( ) ] [ ( ) ] + [ ( ) ] or A I b + b + b where b 0, b, nd b re unctions o the elements ij o A. The solution (roots) o the chrcteristic eqution provides the three eigenvlues Slide No. 3

13 3 Slide No. 4 Eigenvlue Anlysis Exmple : Mtrix Find the eigenvlues o 3 4 A I A Slide No. 5 Eigenvlue Anlysis Exmple (cont d): Mtrix ( ) ( )( ) ( ) det I A The chrcteristic eqution o A is det(a - ), or Solving or, we get -, nd 5 Hence, the eigenvlues o A re - nd 5.

14 Eigenvlue Anlysis Exmple 3: Mtrix Find the eigenvlues o A A I Slide No. 6 Eigenvlue Anlysis Exmple 3 (cont d): Mtrix det ( A I ) ( )( ) ( ) ( ) + 3 The chrcteristic eqution o A is det(a - ), or Solving or, we get + i,nd i Hence, the eigenvlues o A re + i,nd i Note: Even i the elements o A re rel, the eigenvlues my be complex. Slide No. 7 4

15 Methods or Finding the Roots o Equtions. Grphicl Methods. Direct-Serch Method 3. Bisection Method 4. Newton-Rphson Itertion 5. Secnt Method 6. Polynomil Reduction nd Synthetic Division Slide No. 8 Grphicl Methods One method to obtin n pproximte solution is to plot the unction nd determine where it crosses the x xis. This point, which represents the x vlue or which (x) 0, is the root. Although grphicl methods re useul or obtining rough estimtes o roots, they re limited due to their lck o precision. Slide No. 9 5

16 Grphicl Methods Exmple: Flling Prchutist Problem Using the grphicl pproch to determine the drg coeicient or prchutist o mss m 68. kg to hve velocity o 40 m/s ter ree lling or t 0 s. Note tht the ccelertion due to grvity 9.8 m/s. ( ) [ ] c / e m t gm v( t) (4) c Slide No. 30 Grphicl Methods Exmple: Flling Prchutist Problem Eqution 4 cn be rewritten s or or gm ( c) c () c 9.8 c ( c / m) t [ e ] v 0 ( 68.) ( c / 68.)( 0) ( e ) c () c ( e ) c Slide No. 3 6

17 Grphicl Methods Exmple (cont d): Flling Prchutist Problem Vrious vlues o c cn be substituted into the right-hnd side o c () c ( e ) c 40 To check pproximtely which one will mke the unction (x) 0. The ollowing tble nd plot show the results. Slide No. 3 Grphicl Methods Exmple (cont d): Flling Prchutist Problem c () c ( e ) c 40 c (c) c (c ) Slide No. 33 7

18 Grphicl Methods Exmple (cont d): Flling Prchutist Problem (c ) Root Root 4.75 c Slide No. 34 Grphicl Methods Exmple: Eigenvlues The ollowing chrcteristic eqution resulted rom the mtrix A: ( ) A Estimte the eigenvlues (roots) by grphicl pproch. Slide No. 35 8

19 Grphicl Methods Exmple (cont d): Eigenvlues () () () () ( ) Slide No. 36 Grphicl Methods Exmple (cont d): Eigenvlues 0. Root () Root Root ( ) , 0.7, nd 3.9 Slide No. 37 9

CHAPTER 6b. NUMERICAL INTERPOLATION

CHAPTER 6b. NUMERICAL INTERPOLATION CHAPTER 6. NUMERICAL INTERPOLATION A. J. Clrk School o Engineering Deprtment o Civil nd Environmentl Engineering y Dr. Irhim A. Asskk Spring ENCE - Computtion s in Civil Engineering II Deprtment o Civil

More information

Review of Calculus, cont d

Review of Calculus, cont d Jim Lmbers MAT 460 Fll Semester 2009-10 Lecture 3 Notes These notes correspond to Section 1.1 in the text. Review of Clculus, cont d Riemnn Sums nd the Definite Integrl There re mny cses in which some

More information

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by.

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by. NUMERICAL INTEGRATION 1 Introduction The inverse process to differentition in clculus is integrtion. Mthemticlly, integrtion is represented by f(x) dx which stnds for the integrl of the function f(x) with

More information

Chapter 3 Solving Nonlinear Equations

Chapter 3 Solving Nonlinear Equations Chpter 3 Solving Nonliner Equtions 3.1 Introduction The nonliner function of unknown vrible x is in the form of where n could be non-integer. Root is the numericl vlue of x tht stisfies f ( x) 0. Grphiclly,

More information

COSC 3361 Numerical Analysis I Numerical Integration and Differentiation (III) - Gauss Quadrature and Adaptive Quadrature

COSC 3361 Numerical Analysis I Numerical Integration and Differentiation (III) - Gauss Quadrature and Adaptive Quadrature COSC 336 Numericl Anlysis I Numericl Integrtion nd Dierentition III - Guss Qudrture nd Adptive Qudrture Edgr Griel Fll 5 COSC 336 Numericl Anlysis I Edgr Griel Summry o the lst lecture I For pproximting

More information

On Second Derivative-Free Zero Finding Methods

On Second Derivative-Free Zero Finding Methods 010 Americn Control Conerence Mrriott Wterront, Bltimore, MD, USA June 30-July 0, 010 FrC07.4 On Second Derivtive-Free Zero Finding Methods Mohmmed A. Hsn Deprtment o Electricl & Computer Engineering University

More information

The Islamic University of Gaza Faculty of Engineering Civil Engineering Department. Numerical Analysis ECIV Chapter 11

The Islamic University of Gaza Faculty of Engineering Civil Engineering Department. Numerical Analysis ECIV Chapter 11 The Islmic University of Gz Fculty of Engineering Civil Engineering Deprtment Numericl Anlysis ECIV 6 Chpter Specil Mtrices nd Guss-Siedel Associte Prof Mzen Abultyef Civil Engineering Deprtment, The Islmic

More information

CBE 291b - Computation And Optimization For Engineers

CBE 291b - Computation And Optimization For Engineers The University of Western Ontrio Fculty of Engineering Science Deprtment of Chemicl nd Biochemicl Engineering CBE 9b - Computtion And Optimiztion For Engineers Mtlb Project Introduction Prof. A. Jutn Jn

More information

New Expansion and Infinite Series

New Expansion and Infinite Series Interntionl Mthemticl Forum, Vol. 9, 204, no. 22, 06-073 HIKARI Ltd, www.m-hikri.com http://dx.doi.org/0.2988/imf.204.4502 New Expnsion nd Infinite Series Diyun Zhng College of Computer Nnjing University

More information

State space systems analysis (continued) Stability. A. Definitions A system is said to be Asymptotically Stable (AS) when it satisfies

State space systems analysis (continued) Stability. A. Definitions A system is said to be Asymptotically Stable (AS) when it satisfies Stte spce systems nlysis (continued) Stbility A. Definitions A system is sid to be Asymptoticlly Stble (AS) when it stisfies ut () = 0, t > 0 lim xt () 0. t A system is AS if nd only if the impulse response

More information

Numerical Linear Algebra Assignment 008

Numerical Linear Algebra Assignment 008 Numericl Liner Algebr Assignment 008 Nguyen Qun B Hong Students t Fculty of Mth nd Computer Science, Ho Chi Minh University of Science, Vietnm emil. nguyenqunbhong@gmil.com blog. http://hongnguyenqunb.wordpress.com

More information

P 3 (x) = f(0) + f (0)x + f (0) 2. x 2 + f (0) . In the problem set, you are asked to show, in general, the n th order term is a n = f (n) (0)

P 3 (x) = f(0) + f (0)x + f (0) 2. x 2 + f (0) . In the problem set, you are asked to show, in general, the n th order term is a n = f (n) (0) 1 Tylor polynomils In Section 3.5, we discussed how to pproximte function f(x) round point in terms of its first derivtive f (x) evluted t, tht is using the liner pproximtion f() + f ()(x ). We clled this

More information

Lecture 14: Quadrature

Lecture 14: Quadrature Lecture 14: Qudrture This lecture is concerned with the evlution of integrls fx)dx 1) over finite intervl [, b] The integrnd fx) is ssumed to be rel-vlues nd smooth The pproximtion of n integrl by numericl

More information

Best Approximation. Chapter The General Case

Best Approximation. Chapter The General Case Chpter 4 Best Approximtion 4.1 The Generl Cse In the previous chpter, we hve seen how n interpolting polynomil cn be used s n pproximtion to given function. We now wnt to find the best pproximtion to given

More information

Math 520 Final Exam Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008

Math 520 Final Exam Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008 Mth 520 Finl Exm Topic Outline Sections 1 3 (Xio/Dums/Liw) Spring 2008 The finl exm will be held on Tuesdy, My 13, 2-5pm in 117 McMilln Wht will be covered The finl exm will cover the mteril from ll of

More information

We will see what is meant by standard form very shortly

We will see what is meant by standard form very shortly THEOREM: For fesible liner progrm in its stndrd form, the optimum vlue of the objective over its nonempty fesible region is () either unbounded or (b) is chievble t lest t one extreme point of the fesible

More information

20 MATHEMATICS POLYNOMIALS

20 MATHEMATICS POLYNOMIALS 0 MATHEMATICS POLYNOMIALS.1 Introduction In Clss IX, you hve studied polynomils in one vrible nd their degrees. Recll tht if p(x) is polynomil in x, the highest power of x in p(x) is clled the degree of

More information

Jim Lambers MAT 169 Fall Semester Lecture 4 Notes

Jim Lambers MAT 169 Fall Semester Lecture 4 Notes Jim Lmbers MAT 169 Fll Semester 2009-10 Lecture 4 Notes These notes correspond to Section 8.2 in the text. Series Wht is Series? An infinte series, usully referred to simply s series, is n sum of ll of

More information

UNIT 1 FUNCTIONS AND THEIR INVERSES Lesson 1.4: Logarithmic Functions as Inverses Instruction

UNIT 1 FUNCTIONS AND THEIR INVERSES Lesson 1.4: Logarithmic Functions as Inverses Instruction Lesson : Logrithmic Functions s Inverses Prerequisite Skills This lesson requires the use of the following skills: determining the dependent nd independent vribles in n exponentil function bsed on dt from

More information

Matrix Eigenvalues and Eigenvectors September 13, 2017

Matrix Eigenvalues and Eigenvectors September 13, 2017 Mtri Eigenvlues nd Eigenvectors September, 7 Mtri Eigenvlues nd Eigenvectors Lrry Cretto Mechnicl Engineering 5A Seminr in Engineering Anlysis September, 7 Outline Review lst lecture Definition of eigenvlues

More information

Read section 3.3, 3.4 Announcements:

Read section 3.3, 3.4 Announcements: Dte: 3/1/13 Objective: SWBAT pply properties of exponentil functions nd will pply properties of rithms. Bell Ringer: 1. f x = 3x 6, find the inverse, f 1 x., Using your grphing clcultor, Grph 1. f x,f

More information

Numerical Integration

Numerical Integration Chpter 5 Numericl Integrtion Numericl integrtion is the study of how the numericl vlue of n integrl cn be found. Methods of function pproximtion discussed in Chpter??, i.e., function pproximtion vi the

More information

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve Dte: 3/14/13 Objective: SWBAT pply properties of exponentil functions nd will pply properties of rithms. Bell Ringer: Use your clcultor to solve 4 7x =250; 5 3x =500; HW Requests: Properties of Log Equtions

More information

Math& 152 Section Integration by Parts

Math& 152 Section Integration by Parts Mth& 5 Section 7. - Integrtion by Prts Integrtion by prts is rule tht trnsforms the integrl of the product of two functions into other (idelly simpler) integrls. Recll from Clculus I tht given two differentible

More information

NUMERICAL INTEGRATION

NUMERICAL INTEGRATION NUMERICAL INTEGRATION How do we evlute I = f (x) dx By the fundmentl theorem of clculus, if F (x) is n ntiderivtive of f (x), then I = f (x) dx = F (x) b = F (b) F () However, in prctice most integrls

More information

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

SUMMER KNOWHOW STUDY AND LEARNING CENTRE SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18

More information

CHAPTER 2d. MATRICES

CHAPTER 2d. MATRICES CHPTER d. MTRICES University of Bhrin Deprtment of Civil nd rch. Engineering CEG -Numericl Methods in Civil Engineering Deprtment of Civil Engineering University of Bhrin Every squre mtrix hs ssocited

More information

13: Diffusion in 2 Energy Groups

13: Diffusion in 2 Energy Groups 3: Diffusion in Energy Groups B. Rouben McMster University Course EP 4D3/6D3 Nucler Rector Anlysis (Rector Physics) 5 Sept.-Dec. 5 September Contents We study the diffusion eqution in two energy groups

More information

Chapter 1. Chapter 1 1

Chapter 1. Chapter 1 1 Chpter Chpter : Signls nd Systems... 2. Introduction... 2.2 Signls... 3.2. Smpling... 4.2.2 Periodic Signls... 0.2.3 Discrete-Time Sinusoidl Signls... 2.2.4 Rel Exponentil Signls... 5.2.5 Complex Exponentil

More information

Undergraduate Research

Undergraduate Research Undergrdute Reserch A Trigonometric Simpson s Rule By Ctherine Cusimno Kirby nd Sony Stnley Biogrphicl Sketch Ctherine Cusimno Kirby is the dughter of Donn nd Sm Cusimno. Originlly from Vestvi Hills, Albm,

More information

How do you know you have SLE?

How do you know you have SLE? Simultneous Liner Equtions Simultneous Liner Equtions nd Liner Algebr Simultneous liner equtions (SLE s) occur frequently in Sttics, Dynmics, Circuits nd other engineering clsses Need to be ble to, nd

More information

LECTURE. INTEGRATION AND ANTIDERIVATIVE.

LECTURE. INTEGRATION AND ANTIDERIVATIVE. ANALYSIS FOR HIGH SCHOOL TEACHERS LECTURE. INTEGRATION AND ANTIDERIVATIVE. ROTHSCHILD CAESARIA COURSE, 2015/6 1. Integrtion Historiclly, it ws the problem of computing res nd volumes, tht triggered development

More information

Math 1B, lecture 4: Error bounds for numerical methods

Math 1B, lecture 4: Error bounds for numerical methods Mth B, lecture 4: Error bounds for numericl methods Nthn Pflueger 4 September 0 Introduction The five numericl methods descried in the previous lecture ll operte by the sme principle: they pproximte the

More information

Module 2. Analysis of Statically Indeterminate Structures by the Matrix Force Method. Version 2 CE IIT, Kharagpur

Module 2. Analysis of Statically Indeterminate Structures by the Matrix Force Method. Version 2 CE IIT, Kharagpur Module Anlysis of Stticlly Indeterminte Structures by the Mtrix Force Method Version CE IIT, Khrgpur esson 8 The Force Method of Anlysis: Bems Version CE IIT, Khrgpur Instructionl Objectives After reding

More information

Arithmetic & Algebra. NCTM National Conference, 2017

Arithmetic & Algebra. NCTM National Conference, 2017 NCTM Ntionl Conference, 2017 Arithmetic & Algebr Hether Dlls, UCLA Mthemtics & The Curtis Center Roger Howe, Yle Mthemtics & Texs A & M School of Eduction Relted Common Core Stndrds First instnce of vrible

More information

A Criterion on Existence and Uniqueness of Behavior in Electric Circuit

A Criterion on Existence and Uniqueness of Behavior in Electric Circuit Institute Institute of of Advnced Advnced Engineering Engineering nd nd Science Science Interntionl Journl of Electricl nd Computer Engineering (IJECE) Vol 6, No 4, August 2016, pp 1529 1533 ISSN: 2088-8708,

More information

63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1

63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1 3 9. SEQUENCES AND SERIES 63. Representtion of functions s power series Consider power series x 2 + x 4 x 6 + x 8 + = ( ) n x 2n It is geometric series with q = x 2 nd therefore it converges for ll q =

More information

Chapter 3 Single Random Variables and Probability Distributions (Part 2)

Chapter 3 Single Random Variables and Probability Distributions (Part 2) Chpter 3 Single Rndom Vriles nd Proilit Distriutions (Prt ) Contents Wht is Rndom Vrile? Proilit Distriution Functions Cumultive Distriution Function Proilit Densit Function Common Rndom Vriles nd their

More information

Why symmetry? Symmetry is often argued from the requirement that the strain energy must be positive. (e.g. Generalized 3-D Hooke s law)

Why symmetry? Symmetry is often argued from the requirement that the strain energy must be positive. (e.g. Generalized 3-D Hooke s law) Why symmetry? Symmetry is oten rgued rom the requirement tht the strin energy must be positie. (e.g. Generlized -D Hooke s lw) One o the derities o energy principles is the Betti- Mxwell reciprocity theorem.

More information

Matrices, Moments and Quadrature, cont d

Matrices, Moments and Quadrature, cont d Jim Lmbers MAT 285 Summer Session 2015-16 Lecture 2 Notes Mtrices, Moments nd Qudrture, cont d We hve described how Jcobi mtrices cn be used to compute nodes nd weights for Gussin qudrture rules for generl

More information

Chapter 3 MATRIX. In this chapter: 3.1 MATRIX NOTATION AND TERMINOLOGY

Chapter 3 MATRIX. In this chapter: 3.1 MATRIX NOTATION AND TERMINOLOGY Chpter 3 MTRIX In this chpter: Definition nd terms Specil Mtrices Mtrix Opertion: Trnspose, Equlity, Sum, Difference, Sclr Multipliction, Mtrix Multipliction, Determinnt, Inverse ppliction of Mtrix in

More information

1 nonlinear.mcd Find solution root to nonlinear algebraic equation f(x)=0. Instructor: Nam Sun Wang

1 nonlinear.mcd Find solution root to nonlinear algebraic equation f(x)=0. Instructor: Nam Sun Wang nonlinermc Fin solution root to nonliner lgebric eqution ()= Instructor: Nm Sun Wng Bckgroun In science n engineering, we oten encounter lgebric equtions where we wnt to in root(s) tht stisies given eqution

More information

ENGI 3424 Engineering Mathematics Five Tutorial Examples of Partial Fractions

ENGI 3424 Engineering Mathematics Five Tutorial Examples of Partial Fractions ENGI 44 Engineering Mthemtics Five Tutoril Exmples o Prtil Frctions 1. Express x in prtil rctions: x 4 x 4 x 4 b x x x x Both denomintors re liner non-repeted ctors. The cover-up rule my be used: 4 4 4

More information

a a a a a a a a a a a a a a a a a a a a a a a a In this section, we introduce a general formula for computing determinants.

a a a a a a a a a a a a a a a a a a a a a a a a In this section, we introduce a general formula for computing determinants. Section 9 The Lplce Expnsion In the lst section, we defined the determinnt of (3 3) mtrix A 12 to be 22 12 21 22 2231 22 12 21. In this section, we introduce generl formul for computing determinnts. Rewriting

More information

Non-Linear & Logistic Regression

Non-Linear & Logistic Regression Non-Liner & Logistic Regression If the sttistics re boring, then you've got the wrong numbers. Edwrd R. Tufte (Sttistics Professor, Yle University) Regression Anlyses When do we use these? PART 1: find

More information

Lecture 20: Numerical Integration III

Lecture 20: Numerical Integration III cs4: introduction to numericl nlysis /8/0 Lecture 0: Numericl Integrtion III Instructor: Professor Amos Ron Scribes: Mrk Cowlishw, Yunpeng Li, Nthnel Fillmore For the lst few lectures we hve discussed

More information

Vyacheslav Telnin. Search for New Numbers.

Vyacheslav Telnin. Search for New Numbers. Vycheslv Telnin Serch for New Numbers. 1 CHAPTER I 2 I.1 Introduction. In 1984, in the first issue for tht yer of the Science nd Life mgzine, I red the rticle "Non-Stndrd Anlysis" by V. Uspensky, in which

More information

Chapter Direct Method of Interpolation More Examples Civil Engineering

Chapter Direct Method of Interpolation More Examples Civil Engineering Chpter 5. Direct Method of Interpoltion More Exmples Civil Engineering Exmple o mximie ctch of bss in lke, it is suggested to throw the line to the depth of the thermocline. he chrcteristic feture of this

More information

1 Module for Year 10 Secondary School Student Logarithm

1 Module for Year 10 Secondary School Student Logarithm 1 Erthquke Intensity Mesurement (The Richter Scle) Dr Chrles Richter showed tht the lrger the energy of n erthquke hs, the lrger mplitude of ground motion t given distnce. The simple model of Richter

More information

Chapter 4 Contravariance, Covariance, and Spacetime Diagrams

Chapter 4 Contravariance, Covariance, and Spacetime Diagrams Chpter 4 Contrvrince, Covrince, nd Spcetime Digrms 4. The Components of Vector in Skewed Coordintes We hve seen in Chpter 3; figure 3.9, tht in order to show inertil motion tht is consistent with the Lorentz

More information

Chapter 2. Determinants

Chapter 2. Determinants Chpter Determinnts The Determinnt Function Recll tht the X mtrix A c b d is invertible if d-bc0. The expression d-bc occurs so frequently tht it hs nme; it is clled the determinnt of the mtrix A nd is

More information

Lecture 1: Introduction to integration theory and bounded variation

Lecture 1: Introduction to integration theory and bounded variation Lecture 1: Introduction to integrtion theory nd bounded vrition Wht is this course bout? Integrtion theory. The first question you might hve is why there is nything you need to lern bout integrtion. You

More information

On the Decomposition Method for System of Linear Fredholm Integral Equations of the Second Kind

On the Decomposition Method for System of Linear Fredholm Integral Equations of the Second Kind Applied Mthemticl Sciences, Vol. 2, 28, no. 2, 57-62 On the Decomposition Method for System of Liner Fredholm Integrl Equtions of the Second Kind A. R. Vhidi 1 nd M. Mokhtri Deprtment of Mthemtics, Shhr-e-Rey

More information

CMDA 4604: Intermediate Topics in Mathematical Modeling Lecture 19: Interpolation and Quadrature

CMDA 4604: Intermediate Topics in Mathematical Modeling Lecture 19: Interpolation and Quadrature CMDA 4604: Intermedite Topics in Mthemticl Modeling Lecture 19: Interpoltion nd Qudrture In this lecture we mke brief diversion into the res of interpoltion nd qudrture. Given function f C[, b], we sy

More information

1.2. Linear Variable Coefficient Equations. y + b "! = a y + b " Remark: The case b = 0 and a non-constant can be solved with the same idea as above.

1.2. Linear Variable Coefficient Equations. y + b ! = a y + b  Remark: The case b = 0 and a non-constant can be solved with the same idea as above. 1 12 Liner Vrible Coefficient Equtions Section Objective(s): Review: Constnt Coefficient Equtions Solving Vrible Coefficient Equtions The Integrting Fctor Method The Bernoulli Eqution 121 Review: Constnt

More information

Engineering Analysis ENG 3420 Fall Dan C. Marinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00

Engineering Analysis ENG 3420 Fall Dan C. Marinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00 Engineering Anlysis ENG 3420 Fll 2009 Dn C. Mrinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00 Lecture 13 Lst time: Problem solving in preprtion for the quiz Liner Algebr Concepts Vector Spces,

More information

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1 MATH34032: Green s Functions, Integrl Equtions nd the Clculus of Vritions 1 Section 1 Function spces nd opertors Here we gives some brief detils nd definitions, prticulrly relting to opertors. For further

More information

Improper Integrals, and Differential Equations

Improper Integrals, and Differential Equations Improper Integrls, nd Differentil Equtions October 22, 204 5.3 Improper Integrls Previously, we discussed how integrls correspond to res. More specificlly, we sid tht for function f(x), the region creted

More information

Polynomials and Division Theory

Polynomials and Division Theory Higher Checklist (Unit ) Higher Checklist (Unit ) Polynomils nd Division Theory Skill Achieved? Know tht polynomil (expression) is of the form: n x + n x n + n x n + + n x + x + 0 where the i R re the

More information

A Modified ADM for Solving Systems of Linear Fredholm Integral Equations of the Second Kind

A Modified ADM for Solving Systems of Linear Fredholm Integral Equations of the Second Kind Applied Mthemticl Sciences, Vol. 6, 2012, no. 26, 1267-1273 A Modified ADM for Solving Systems of Liner Fredholm Integrl Equtions of the Second Kind A. R. Vhidi nd T. Dmercheli Deprtment of Mthemtics,

More information

13.4 Work done by Constant Forces

13.4 Work done by Constant Forces 13.4 Work done by Constnt Forces We will begin our discussion of the concept of work by nlyzing the motion of n object in one dimension cted on by constnt forces. Let s consider the following exmple: push

More information

Lecture 10. Solution of Nonlinear Equations - II

Lecture 10. Solution of Nonlinear Equations - II Fied point Poblems Lectue Solution o Nonline Equtions - II Given unction g : R R, vlue such tht gis clled ied point o the unction g, since is unchnged when g is pplied to it. Whees with nonline eqution

More information

Z b. f(x)dx. Yet in the above two cases we know what f(x) is. Sometimes, engineers want to calculate an area by computing I, but...

Z b. f(x)dx. Yet in the above two cases we know what f(x) is. Sometimes, engineers want to calculate an area by computing I, but... Chpter 7 Numericl Methods 7. Introduction In mny cses the integrl f(x)dx cn be found by finding function F (x) such tht F 0 (x) =f(x), nd using f(x)dx = F (b) F () which is known s the nlyticl (exct) solution.

More information

Review of Gaussian Quadrature method

Review of Gaussian Quadrature method Review of Gussin Qudrture method Nsser M. Asi Spring 006 compiled on Sundy Decemer 1, 017 t 09:1 PM 1 The prolem To find numericl vlue for the integrl of rel vlued function of rel vrile over specific rnge

More information

Fredholm Integral Equations of the First Kind Solved by Using the Homotopy Perturbation Method

Fredholm Integral Equations of the First Kind Solved by Using the Homotopy Perturbation Method Int. Journl of Mth. Anlysis, Vol. 5, 211, no. 19, 935-94 Fredholm Integrl Equtions of the First Kind Solved by Using the Homotopy Perturbtion Method Seyyed Mhmood Mirzei Deprtment of Mthemtics, Fculty

More information

Elements of Matrix Algebra

Elements of Matrix Algebra Elements of Mtrix Algebr Klus Neusser Kurt Schmidheiny September 30, 2015 Contents 1 Definitions 2 2 Mtrix opertions 3 3 Rnk of Mtrix 5 4 Specil Functions of Qudrtic Mtrices 6 4.1 Trce of Mtrix.........................

More information

Math 100 Review Sheet

Math 100 Review Sheet Mth 100 Review Sheet Joseph H. Silvermn December 2010 This outline of Mth 100 is summry of the mteril covered in the course. It is designed to be study id, but it is only n outline nd should be used s

More information

Review of basic calculus

Review of basic calculus Review of bsic clculus This brief review reclls some of the most importnt concepts, definitions, nd theorems from bsic clculus. It is not intended to tech bsic clculus from scrtch. If ny of the items below

More information

Overview of Calculus I

Overview of Calculus I Overview of Clculus I Prof. Jim Swift Northern Arizon University There re three key concepts in clculus: The limit, the derivtive, nd the integrl. You need to understnd the definitions of these three things,

More information

Continuous Random Variable X:

Continuous Random Variable X: Continuous Rndom Vrile : The continuous rndom vrile hs its vlues in n intervl, nd it hs proility distriution unction or proility density unction p.d. stisies:, 0 & d Which does men tht the totl re under

More information

Part I: Basic Concepts of Thermodynamics

Part I: Basic Concepts of Thermodynamics Prt I: Bsic Concepts o Thermodynmics Lecture 4: Kinetic Theory o Gses Kinetic Theory or rel gses 4-1 Kinetic Theory or rel gses Recll tht or rel gses: (i The volume occupied by the molecules under ordinry

More information

Lecture Solution of a System of Linear Equation

Lecture Solution of a System of Linear Equation ChE Lecture Notes, Dept. of Chemicl Engineering, Univ. of TN, Knoville - D. Keffer, 5/9/98 (updted /) Lecture 8- - Solution of System of Liner Eqution 8. Why is it importnt to e le to solve system of liner

More information

Orthogonal Polynomials

Orthogonal Polynomials Mth 4401 Gussin Qudrture Pge 1 Orthogonl Polynomils Orthogonl polynomils rise from series solutions to differentil equtions, lthough they cn be rrived t in vriety of different mnners. Orthogonl polynomils

More information

Introduction to Numerical Analysis

Introduction to Numerical Analysis Introduction to Numericl Anlysis Doron Levy Deprtment of Mthemtics nd Center for Scientific Computtion nd Mthemticl Modeling (CSCAMM) University of Mrylnd June 14, 2012 D. Levy CONTENTS Contents 1 Introduction

More information

1 The Riemann Integral

1 The Riemann Integral The Riemnn Integrl. An exmple leding to the notion of integrl (res) We know how to find (i.e. define) the re of rectngle (bse height), tringle ( (sum of res of tringles). But how do we find/define n re

More information

1 Numerical integration

1 Numerical integration 1 Numericl integrtion 1.1 Introduction The term numericl integrtion reers to brod mily o lgorithms to compute numericl pproximtion to deinite (Riemnn) integrl. Generlly, the integrl is pproximted by weighted

More information

Abstract inner product spaces

Abstract inner product spaces WEEK 4 Abstrct inner product spces Definition An inner product spce is vector spce V over the rel field R equipped with rule for multiplying vectors, such tht the product of two vectors is sclr, nd the

More information

Module 6: LINEAR TRANSFORMATIONS

Module 6: LINEAR TRANSFORMATIONS Module 6: LINEAR TRANSFORMATIONS. Trnsformtions nd mtrices Trnsformtions re generliztions of functions. A vector x in some set S n is mpped into m nother vector y T( x). A trnsformtion is liner if, for

More information

different methods (left endpoint, right endpoint, midpoint, trapezoid, Simpson s).

different methods (left endpoint, right endpoint, midpoint, trapezoid, Simpson s). Mth 1A with Professor Stnkov Worksheet, Discussion #41; Wednesdy, 12/6/217 GSI nme: Roy Zho Problems 1. Write the integrl 3 dx s limit of Riemnn sums. Write it using 2 intervls using the 1 x different

More information

4.5 JACOBI ITERATION FOR FINDING EIGENVALUES OF A REAL SYMMETRIC MATRIX. be a real symmetric matrix. ; (where we choose θ π for.

4.5 JACOBI ITERATION FOR FINDING EIGENVALUES OF A REAL SYMMETRIC MATRIX. be a real symmetric matrix. ; (where we choose θ π for. 4.5 JACOBI ITERATION FOR FINDING EIGENVALUES OF A REAL SYMMETRIC MATRIX Some reliminries: Let A be rel symmetric mtrix. Let Cos θ ; (where we choose θ π for Cos θ 4 purposes of convergence of the scheme)

More information

STEP FUNCTIONS, DELTA FUNCTIONS, AND THE VARIATION OF PARAMETERS FORMULA. 0 if t < 0, 1 if t > 0.

STEP FUNCTIONS, DELTA FUNCTIONS, AND THE VARIATION OF PARAMETERS FORMULA. 0 if t < 0, 1 if t > 0. STEP FUNCTIONS, DELTA FUNCTIONS, AND THE VARIATION OF PARAMETERS FORMULA STEPHEN SCHECTER. The unit step function nd piecewise continuous functions The Heviside unit step function u(t) is given by if t

More information

Numerical Analysis: Trapezoidal and Simpson s Rule

Numerical Analysis: Trapezoidal and Simpson s Rule nd Simpson s Mthemticl question we re interested in numericlly nswering How to we evlute I = f (x) dx? Clculus tells us tht if F(x) is the ntiderivtive of function f (x) on the intervl [, b], then I =

More information

FBR Neutronics: Breeding potential, Breeding Ratio, Breeding Gain and Doubling time

FBR Neutronics: Breeding potential, Breeding Ratio, Breeding Gain and Doubling time FBR eutronics: Breeding potentil, Breeding Rtio, Breeding Gin nd Doubling time K.S. Rjn Proessor, School o Chemicl & Biotechnology SASTRA University Joint Inititive o IITs nd IISc Funded by MHRD Pge 1

More information

Ordinary differential equations

Ordinary differential equations Ordinry differentil equtions Introduction to Synthetic Biology E Nvrro A Montgud P Fernndez de Cordob JF Urchueguí Overview Introduction-Modelling Bsic concepts to understnd n ODE. Description nd properties

More information

Multivariate problems and matrix algebra

Multivariate problems and matrix algebra University of Ferrr Stefno Bonnini Multivrite problems nd mtrix lgebr Multivrite problems Multivrite sttisticl nlysis dels with dt contining observtions on two or more chrcteristics (vribles) ech mesured

More information

Best Approximation in the 2-norm

Best Approximation in the 2-norm Jim Lmbers MAT 77 Fll Semester 1-11 Lecture 1 Notes These notes correspond to Sections 9. nd 9.3 in the text. Best Approximtion in the -norm Suppose tht we wish to obtin function f n (x) tht is liner combintion

More information

Introduction to Finite Element Method

Introduction to Finite Element Method Introduction to Finite Element Method Introductory Course on Multiphysics Modelling TOMASZ G. ZIELIŃSKI bluebox.ippt.pn.pl/ tzielins/ Tble of Contents 1 Introduction 1 1.1 Motivtion nd generl concepts.............

More information

Chapter 7 Notes, Stewart 8e. 7.1 Integration by Parts Trigonometric Integrals Evaluating sin m x cos n (x) dx...

Chapter 7 Notes, Stewart 8e. 7.1 Integration by Parts Trigonometric Integrals Evaluating sin m x cos n (x) dx... Contents 7.1 Integrtion by Prts................................... 2 7.2 Trigonometric Integrls.................................. 8 7.2.1 Evluting sin m x cos n (x)......................... 8 7.2.2 Evluting

More information

More precisely, given the collection fx g, with Eucliden distnces between pirs (; b) of ptterns: = p (x? x b ) ; one hs to nd mp, ' : R n distnce-erro

More precisely, given the collection fx g, with Eucliden distnces between pirs (; b) of ptterns: = p (x? x b ) ; one hs to nd mp, ' : R n distnce-erro Improved Multidimensionl Scling Anlysis Using Neurl Networks with Distnce-Error Bckpropgtion Llus Grrido (), Sergio Gomez () nd Jume Roc () () Deprtment d'estructur i Constituents de l Mteri/IFAE Universitt

More information

Math 8 Winter 2015 Applications of Integration

Math 8 Winter 2015 Applications of Integration Mth 8 Winter 205 Applictions of Integrtion Here re few importnt pplictions of integrtion. The pplictions you my see on n exm in this course include only the Net Chnge Theorem (which is relly just the Fundmentl

More information

ADVANCEMENT OF THE CLOSELY COUPLED PROBES POTENTIAL DROP TECHNIQUE FOR NDE OF SURFACE CRACKS

ADVANCEMENT OF THE CLOSELY COUPLED PROBES POTENTIAL DROP TECHNIQUE FOR NDE OF SURFACE CRACKS ADVANCEMENT OF THE CLOSELY COUPLED PROBES POTENTIAL DROP TECHNIQUE FOR NDE OF SURFACE CRACKS F. Tkeo 1 nd M. Sk 1 Hchinohe Ntionl College of Technology, Hchinohe, Jpn; Tohoku University, Sendi, Jpn Abstrct:

More information

Definite integral. Mathematics FRDIS MENDELU

Definite integral. Mathematics FRDIS MENDELU Definite integrl Mthemtics FRDIS MENDELU Simon Fišnrová Brno 1 Motivtion - re under curve Suppose, for simplicity, tht y = f(x) is nonnegtive nd continuous function defined on [, b]. Wht is the re of the

More information

Hermite-Hadamard type inequalities for harmonically convex functions

Hermite-Hadamard type inequalities for harmonically convex functions Hcettepe Journl o Mthemtics nd Sttistics Volume 43 6 4 935 94 Hermite-Hdmrd type ineulities or hrmoniclly convex unctions İmdt İşcn Abstrct The uthor introduces the concept o hrmoniclly convex unctions

More information

SOLVING SYSTEMS OF EQUATIONS, ITERATIVE METHODS

SOLVING SYSTEMS OF EQUATIONS, ITERATIVE METHODS ELM Numericl Anlysis Dr Muhrrem Mercimek SOLVING SYSTEMS OF EQUATIONS, ITERATIVE METHODS ELM Numericl Anlysis Some of the contents re dopted from Lurene V. Fusett, Applied Numericl Anlysis using MATLAB.

More information

B.Sc. in Mathematics (Ordinary)

B.Sc. in Mathematics (Ordinary) R48/0 DUBLIN INSTITUTE OF TECHNOLOGY KEVIN STREET, DUBLIN 8 B.Sc. in Mthemtics (Ordinry) SUPPLEMENTAL EXAMINATIONS 01 Numericl Methods Dr. D. Mckey Dr. C. Hills Dr. E.A. Cox Full mrks for complete nswers

More information

Numerical Integration

Numerical Integration Chpter 1 Numericl Integrtion Numericl differentition methods compute pproximtions to the derivtive of function from known vlues of the function. Numericl integrtion uses the sme informtion to compute numericl

More information

Numerical Analysis. 10th ed. R L Burden, J D Faires, and A M Burden

Numerical Analysis. 10th ed. R L Burden, J D Faires, and A M Burden Numericl Anlysis 10th ed R L Burden, J D Fires, nd A M Burden Bemer Presenttion Slides Prepred by Dr. Annette M. Burden Youngstown Stte University July 9, 2015 Chpter 4.1: Numericl Differentition 1 Three-Point

More information

MAT 772: Numerical Analysis. James V. Lambers

MAT 772: Numerical Analysis. James V. Lambers MAT 772: Numericl Anlysis Jmes V. Lmbers August 23, 2016 2 Contents 1 Solution of Equtions by Itertion 7 1.1 Nonliner Equtions....................... 7 1.1.1 Existence nd Uniqueness................ 7 1.1.2

More information

Integral points on the rational curve

Integral points on the rational curve Integrl points on the rtionl curve y x bx c x ;, b, c integers. Konstntine Zeltor Mthemtics University of Wisconsin - Mrinette 750 W. Byshore Street Mrinette, WI 5443-453 Also: Konstntine Zeltor P.O. Box

More information

Section 4.8. D v(t j 1 ) t. (4.8.1) j=1

Section 4.8. D v(t j 1 ) t. (4.8.1) j=1 Difference Equtions to Differentil Equtions Section.8 Distnce, Position, nd the Length of Curves Although we motivted the definition of the definite integrl with the notion of re, there re mny pplictions

More information