MATHEMATICAL METHODS FOURIER SERIES

Similar documents
AN INTRODUCTION TO NUMERICAL METHODS AND ANALYSIS

Mean value theorem, Taylors Theorem, Maxima and Minima.

Numerical Analysis An Introduction

Applied Linear Algebra I Review page 1

Numerical Analysis Introduction. Student Audience. Prerequisites. Technology.

GEC320 COURSE COMPACT. Four hours per week for 15 weeks (60 hours)

376 CURRICULUM AND SYLLABUS for Classes XI & XII

Precalculus REVERSE CORRELATION. Content Expectations for. Precalculus. Michigan CONTENT EXPECTATIONS FOR PRECALCULUS CHAPTER/LESSON TITLES

Sequence of Mathematics Courses

Essential Mathematics for Computer Graphics fast

Numerical Methods for Engineers

NUMERICAL METHODS TOPICS FOR RESEARCH PAPERS

Recall that two vectors in are perpendicular or orthogonal provided that their dot

Thnkwell s Homeschool Precalculus Course Lesson Plan: 36 weeks

MATHEMATICS (MATH) 3. Provides experiences that enable graduates to find employment in sciencerelated

Nonlinear Iterative Partial Least Squares Method

Elementary Differential Equations and Boundary Value Problems. 10th Edition International Student Version

by the matrix A results in a vector which is a reflection of the given

Unit 4: 15 Progression : Definition of A.P. & G.P., To find Tn & Sn, Simple practical commercial problems.

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

Arithmetic and Algebra of Matrices

ALGEBRAIC EIGENVALUE PROBLEM

SUBSIDIARY COURSES BEING TAUGHT TO THE STUDENTS OF OTHER DEPARTMENTS

Mathematics (MAT) MAT 061 Basic Euclidean Geometry 3 Hours. MAT 051 Pre-Algebra 4 Hours

Computer programming course in the Department of Physics, University of Calcutta

Content. Chapter 4 Functions Basic concepts on real functions 62. Credits 11

Numerical Recipes in C++

SCHWEITZER ENGINEERING LABORATORIES, COMERCIAL LTDA.

November 16, Interpolation, Extrapolation & Polynomial Approximation

Chapter 6. Orthogonality

UNIVERSITY OF PUNE, PUNE BOARD OF STUDIES IN MATHEMATICS SYLLABUS

1 Introduction to Matrices

Continued Fractions and the Euclidean Algorithm

MATHEMATICAL METHODS OF STATISTICS

(Refer Slide Time: 1:42)

POLYNOMIAL HISTOPOLATION, SUPERCONVERGENT DEGREES OF FREEDOM, AND PSEUDOSPECTRAL DISCRETE HODGE OPERATORS

South Carolina College- and Career-Ready (SCCCR) Pre-Calculus

Similarity and Diagonalization. Similar Matrices

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all.

NUMERICAL ANALYSIS PROGRAMS

ORDINARY DIFFERENTIAL EQUATIONS

BookTOC.txt. 1. Functions, Graphs, and Models. Algebra Toolbox. Sets. The Real Numbers. Inequalities and Intervals on the Real Number Line

MAT 200, Midterm Exam Solution. a. (5 points) Compute the determinant of the matrix A =

Linear-Quadratic Optimal Controller 10.3 Optimal Linear Control Systems

Numerical Methods. Numerical Methods. for Engineers. for Engineers. Steven C. Chapra Raymond P. Canale. Chapra Canale. Sixth Edition.

Appendix 3 IB Diploma Programme Course Outlines

UNIVERSITY OF PUNE, PUNE. BOARD OF STUDIES IN MATHEMATICS. Syllabus for S.Y.B.Sc. Subject: MATHEMATICS. (With effect from June 2014)

MATH BOOK OF PROBLEMS SERIES. New from Pearson Custom Publishing!

Au = = = 3u. Aw = = = 2w. so the action of A on u and w is very easy to picture: it simply amounts to a stretching by 3 and 2, respectively.

DRAFT. Further mathematics. GCE AS and A level subject content

SOLVING LINEAR SYSTEMS

Indiana State Core Curriculum Standards updated 2009 Algebra I

Elementary Linear Algebra

A note on companion matrices

Natural cubic splines

Prentice Hall Mathematics: Algebra Correlated to: Utah Core Curriculum for Math, Intermediate Algebra (Secondary)

Introduction to Matrix Algebra

Linear Algebra Done Wrong. Sergei Treil. Department of Mathematics, Brown University

Linear Algebra Review. Vectors

3. Interpolation. Closing the Gaps of Discretization... Beyond Polynomials

Mathematics Course 111: Algebra I Part IV: Vector Spaces

The Quantum Harmonic Oscillator Stephen Webb

Diablo Valley College Catalog

How To Prove The Dirichlet Unit Theorem

MTH 437/537 Introduction to Numerical Analysis I Fall 2015

A Level Further Mathematics

a 11 x 1 + a 12 x a 1n x n = b 1 a 21 x 1 + a 22 x a 2n x n = b 2.

Higher Education Math Placement

NEW YORK STATE TEACHER CERTIFICATION EXAMINATIONS

Lecture 5 Principal Minors and the Hessian

[1] Diagonal factorization

Numerical Methods for Solving Systems of Nonlinear Equations

Mathematics INDIVIDUAL PROGRAM INFORMATION Macomb1 ( )

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.

CHAPTER 8 FACTOR EXTRACTION BY MATRIX FACTORING TECHNIQUES. From Exploratory Factor Analysis Ledyard R Tucker and Robert C.

Please start the slide show from the beginning to use links. Click here for active links to various courses

Mathematics. Mathematics MATHEMATICS Sacramento City College Catalog. Degree: A.S. Mathematics AS-T Mathematics for Transfer

Piecewise Cubic Splines

Math Course Descriptions & Student Learning Outcomes

DOKUZ EYLUL UNIVERSITY GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES DIRECTORATE COURSE / MODULE / BLOCK DETAILS ACADEMIC YEAR / SEMESTER

Georgia Department of Education Kathy Cox, State Superintendent of Schools 7/19/2005 All Rights Reserved 1

College of Arts and Sciences. Mathematics

Prentice Hall Algebra Correlated to: Colorado P-12 Academic Standards for High School Mathematics, Adopted 12/2009

Abstract: We describe the beautiful LU factorization of a square matrix (or how to write Gaussian elimination in terms of matrix multiplication).

the points are called control points approximating curve

METNUMER - Numerical Methods

Notes on Determinant

Linear Algebra Done Wrong. Sergei Treil. Department of Mathematics, Brown University

Partial Fractions. Combining fractions over a common denominator is a familiar operation from algebra:

The Characteristic Polynomial

CHAPTER 2. Eigenvalue Problems (EVP s) for ODE s

SIGNAL PROCESSING & SIMULATION NEWSLETTER

Applied Computational Economics and Finance

UNIVERSITY GRADUATE STUDIES PROGRAM SILLIMAN UNIVERSITY DUMAGUETE CITY. Master of Science in Mathematics

1 VECTOR SPACES AND SUBSPACES

G.A. Pavliotis. Department of Mathematics. Imperial College London

COWLEY COLLEGE & Area Vocational Technical School

Systems of Linear Equations

Transcription:

MATHEMATICAL METHODS FOURIER SERIES I YEAR B.Tech By Mr. Y. Prabhaker Reddy Asst. Professor of Mathematics Guru Nanak Engineering College Ibrahimpatnam, Hyderabad.

SYLLABUS OF MATHEMATICAL METHODS (as per JNTU Hyderabad) Name of the Unit Unit-I Solution of Linear systems Unit-II Eigen values and Eigen vectors Unit-III Linear Transformations Unit-IV Solution of Nonlinear Systems Unit-V Curve fitting & Numerical Integration Unit-VI Numerical solution of ODE Unit-VII Fourier Series Unit-VIII Partial Differential Equations Name of the Topic Matrices and Linear system of equations: Elementary row transformations Rank Echelon form, Normal form Solution of Linear Systems Direct Methods LU Decomposition from Gauss Elimination Solution of Tridiagonal systems Solution of Linear Systems. Eigen values, Eigen vectors properties Condition number of Matrix, Cayley Hamilton Theorem (without proof) Inverse and powers of a matrix by Cayley Hamilton theorem Diagonalization of matrix Calculation of powers of matrix Model and spectral matrices. Real Matrices, Symmetric, skew symmetric, Orthogonal, Linear Transformation - Orthogonal Transformation. Complex Matrices, Hermition and skew Hermition matrices, Unitary Matrices - Eigen values and Eigen vectors of complex matrices and their properties. Quadratic forms - Reduction of quadratic form to canonical form, Rank, Positive, negative and semi definite, Index, signature, Sylvester law, Singular value decomposition. Solution of Algebraic and Transcendental Equations- Introduction: The Bisection Method The Method of False Position The Iteration Method - Newton Raphson Method Interpolation:Introduction-Errors in Polynomial Interpolation - Finite differences- Forward difference, Backward differences, Central differences, Symbolic relations and separation of symbols-difference equations Differences of a polynomial - Newton s Formulae for interpolation - Central difference interpolation formulae - Gauss Central Difference Formulae - Lagrange s Interpolation formulae- B. Spline interpolation, Cubic spline. Curve Fitting: Fitting a straight line - Second degree curve - Exponential curve - Power curve by method of least squares. Numerical Integration: Numerical Differentiation-Simpson s 3/8 Rule, Integration, Evaluation of Principal value integrals, Generalized Quadrature. Gaussian Solution by Taylor s series - Picard s Method of successive approximation- Euler s Method -Runge kutta Methods, Predictor Corrector Methods, Adams- Bashforth Method. Determination of Fourier coefficients - Fourier series-even and odd functions - Fourier series in an arbitrary interval - Even and odd periodic continuation - Halfrange Fourier sine and cosine expansions. Introduction and formation of PDE by elimination of arbitrary constants and arbitrary functions - Solutions of first order linear equation - Non linear equations - Method of separation of variables for second order equations - Two dimensional wave equation.

CONTENTS UNIT-VII FOURIER SERIES Introduction to Fourier Series Periodic Functions Euler s Formulae Definition of Fourier Series Fourier Series defined in various Intervals Half Range Fourier Series Important Formulae Problems on Fourier series

FOURIER SERIES Fourier Series is an infinite series representation of periodic function in terms of the trigonometric sine and cosine functions. Most of the single valued functions which occur in applied mathematics can be expressed in the form of Fourier series, which is in terms of sines and cosines. Fourier series is to be expressed in terms of periodic functions- sines and cosines. Fourier series is a very powerful method to solve ordinary and partial differential equations, particularly with periodic functions appearing as non-homogeneous terms. We know that, Taylor s series expansion is valid only for functions which are continuous and differentiable. Fourier series is possible not only for continuous functions but also for periodic functions, functions which are discontinuous in their values and derivatives. Further, because of the periodic nature, Fourier series constructed for one period is valid for all values. Periodic Functions A function is said to be periodic function with period if for all,, and is the least of such values. Ex: 1) are periodic functions with period. 2) are periodic functions with period. Euler s Formulae The Fourier Series for the function in the interval is given by where These values are known as Euler s Formulae.

CONDITIONS FOR FOURIER EXPANSION A function defined in has a valid Fourier series expansion of the form Where are constants, provided 1) is well defined and single-valued, except possibly at a finite number of point in the interval. 2) has finite number of finite discontinuities in the interval in. 3) has finite number of finite maxima and minima. Note: The above conditions are valid for the function defined in the Intervals. Consider any two, All these have a common period. Here = All these have a common period. These are called complete set of orthogonal functions. Definition of Fourier series Let be a function defined in. Let, then the Fourier Series of is given by where These values are called as Fourier coefficients of in. Let be a function defined in. Let, then the Fourier Series of is given by where These values are called as Fourier coefficients of in.

Let be a function defined in. Let, then the Fourier Series of where is given by These values are called as Fourier coefficients of in. Let be a function defined in. Let, then the Fourier Series of is given by where These values are called as Fourier coefficients of in. FOURIER SERIES FOR EVEN AND ODD FUNCTIONS We know that if be a function defined in. Let, then the Fourier Series of is given by where These values are called as Fourier coefficients of in. Case (i): When is an even function then, Since is an even function, is an even function Product of two even functions is even Now, is an odd function, is an even function Product of odd and even is odd

Thus, if a function is even in, its Fourier series expansion contains only cosine terms. Hence Fourier Series is given by where Case (ii): When is an Odd Function then, Since is an even function, is an odd function Product of even and odd is even Now, is an odd function, is an odd function Product of two odd functions is even Thus, if a function is Odd in, its Fourier series expansion contains only sine terms. Hence, if is odd function defined in, can be expanded as a series of the form HALF RANGE FOURIER SERIES Half Range Fourier Sine Series defined in : The Fourier half range sine series in is given by This is Similar to the Fourier series defined for odd function in

Half Range Fourier Cosine Series defined in : The Fourier half range Cosine series in is given by This is Similar to the Fourier series defined for even function in Half Range Fourier Sine Series defined in : The Fourier half range sine series in is given by This is Similar to the Fourier series defined for odd function in Half Range Fourier Cosine Series defined in : The Fourier half range Cosine series in is given by This is Similar to the Fourier series defined for even function in Important Formulae Here Even function means: If, then is called as even function Odd function means : If, then is called as odd function., Also

Problems on Fourier Series 1) Find the Fourier series to represent in the interval Sol: We know that, the Fourier series of defined in the interval is given by Here, Now, Again,

Again, This is the Fourier series for the function Hence the result

2) Find the Fourier series of the periodic function defined as Hence deduce that Sol: We know that, the Fourier series of defined in the interval is given by Here, Now, Also,

Again, Hence, the Fourier series for given is given by

Deduction: Put in the above function, we get Since, is discontinuous at, Hence, Hence the result 3) Expand the function as Fourier series in. Hence deduce that Sol: We know that, the Fourier series of defined in the interval is given by Here, Now,

Again, Again, Hence, the Fourier series for given is given by Deduction: Put in the above equation, we get Hence the Result