UNIT II SOLUTION OF NON-LINEAR AND SIMULTANEOUS LINEAR EQUATION

Similar documents
SRI RAMAKRISHNA INSTITUTE OF TECHNOLOGY, COIMBATORE- 10 DEPARTMENT OF SCIENCE AND HUMANITIES B.E - EEE & CIVIL UNIT I

The iteration formula for to find the root of the equation

Hence a root lies between 1 and 2. Since f a is negative and f(x 0 ) is positive The root lies between a and x 0 i.e. 1 and 1.

SBAME CALCULUS OF FINITE DIFFERENCES AND NUMERICAL ANLAYSIS-I Units : I-V

SRI RAMAKRISHNA INSTITUTE OF TECHNOLOGY DEPARTMENT OF SCIENCE & HUMANITIES STATISTICS & NUMERICAL METHODS TWO MARKS

UNIT - 2 Unit-02/Lecture-01

SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS BISECTION METHOD

Virtual University of Pakistan

CHAPTER-II ROOTS OF EQUATIONS

M.SC. PHYSICS - II YEAR

Page No.1. MTH603-Numerical Analysis_ Muhammad Ishfaq

Program : M.A./M.Sc. (Mathematics) M.A./M.Sc. (Final) Paper Code:MT-08 Numerical Analysis Section A (Very Short Answers Questions)

Mathematical Methods for Numerical Analysis and Optimization

MTH603 FAQ + Short Questions Answers.

Lecture 44. Better and successive approximations x2, x3,, xn to the root are obtained from

Previous Year Questions & Detailed Solutions

Numerical Methods Dr. Sanjeev Kumar Department of Mathematics Indian Institute of Technology Roorkee Lecture No 7 Regula Falsi and Secant Methods

Root Finding (and Optimisation)

Question Bank (I scheme )

Solution of Nonlinear Equations

Numerical Methods. Root Finding

MTH603 - Numerical Analysis Solved final Term Papers For Final Term Exam

SOLVING EQUATIONS OF ONE VARIABLE

Non-linear least squares

Subbalakshmi Lakshmipathy College of Science. Department of Mathematics

Roots of Equations. ITCS 4133/5133: Introduction to Numerical Methods 1 Roots of Equations

Exact and Approximate Numbers:

Numerical and Statistical Methods

Numerical and Statistical Methods

1. to apply Simpson s 1/3 rule, the number of intervals in the following must be Answer: (select your correct answer)

Solving Non-Linear Equations (Root Finding)

Practical Numerical Analysis: Sheet 3 Solutions

by Martin Mendez, UASLP Copyright 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

COURSE Numerical methods for solving linear systems. Practical solving of many problems eventually leads to solving linear systems.

COURSE Iterative methods for solving linear systems

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF MATHEMATICS ACADEMIC YEAR / EVEN SEMESTER QUESTION BANK

Zeroes of Transcendental and Polynomial Equations. Bisection method, Regula-falsi method and Newton-Raphson method

Justify all your answers and write down all important steps. Unsupported answers will be disregarded.

Numerical Methods. Scientists. Engineers

Numerical Analysis Solution of Algebraic Equation (non-linear equation) 1- Trial and Error. 2- Fixed point

Numerical Analysis MTH603

The Solution of Linear Systems AX = B

Appendix 8 Numerical Methods for Solving Nonlinear Equations 1

10.2 ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS. The Jacobi Method

SECTION 5: POWER FLOW. ESE 470 Energy Distribution Systems

Gauss-Seidel method. Dr. Motilal Panigrahi. Dr. Motilal Panigrahi, Nirma University

LINEAR SYSTEMS (11) Intensive Computation

Solution of Algebric & Transcendental Equations

JACOBI S ITERATION METHOD

USHA RAMA COLLEGE OF ENGINEERING & TECHNOLOGY

Solving Linear Systems of Equations

PART I Lecture Notes on Numerical Solution of Root Finding Problems MATH 435

Iterative Methods. Splitting Methods

Numerical Analysis & Computer Programming

Linear Algebraic Equations

2.29 Numerical Fluid Mechanics Spring 2015 Lecture 4

Department of Applied Mathematics and Theoretical Physics. AMA 204 Numerical analysis. Exam Winter 2004

Fixed Points and Contractive Transformations. Ron Goldman Department of Computer Science Rice University

STATISTICS AND NUMERICAL METHODS

NOTES FOR NUMERICAL METHODS MUHAMMAD USMAN HAMID

Math Numerical Analysis Mid-Term Test Solutions

LU Factorization. Marco Chiarandini. DM559 Linear and Integer Programming. Department of Mathematics & Computer Science University of Southern Denmark

Root Finding: Close Methods. Bisection and False Position Dr. Marco A. Arocha Aug, 2014

Examination paper for TMA4130 Matematikk 4N

p 1 p 0 (p 1, f(p 1 )) (p 0, f(p 0 )) The geometric construction of p 2 for the se- cant method.

lecture 2 and 3: algorithms for linear algebra

(f(x) P 3 (x)) dx. (a) The Lagrange formula for the error is given by

Engineering Mathematics

Unit I (Testing of Hypothesis)

Excel for Scientists and Engineers Numerical Method s. E. Joseph Billo

MALLA REDDY ENGINEERING COLLEGE

Numerical Analysis MTH603. Virtual University of Pakistan Knowledge beyond the boundaries

Numerical Analysis: Solutions of System of. Linear Equation. Natasha S. Sharma, PhD

TMA4125 Matematikk 4N Spring 2017

Solution of Linear systems

EE 581 Power Systems. Admittance Matrix: Development, Direct and Iterative solutions

MA3232 Numerical Analysis Week 9. James Cooley (1926-)

Bisection and False Position Dr. Marco A. Arocha Aug, 2014

Gauss-Jordan elimination ( used in the videos below) stops when the augmented coefficient

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University

CS 323: Numerical Analysis and Computing

Next topics: Solving systems of linear equations

Determining the Roots of Non-Linear Equations Part I

MATH 3795 Lecture 12. Numerical Solution of Nonlinear Equations.

MAHARASHTRA STATE BOARD OF TECHNICAL EDUCATION

Chapter 4. Solution of Non-linear Equation. Module No. 1. Newton s Method to Solve Transcendental Equation

Linear Algebraic Equations

EAD 115. Numerical Solution of Engineering and Scientific Problems. David M. Rocke Department of Applied Science

1 Eigenvalues and eigenvectors

Today s class. Linear Algebraic Equations LU Decomposition. Numerical Methods, Fall 2011 Lecture 8. Prof. Jinbo Bi CSE, UConn

Example - Newton-Raphson Method

School of Sciences Indira Gandhi National Open University Maidan Garhi, New Delhi (For January 2012 cycle)

MAC1105-College Algebra. Chapter 5-Systems of Equations & Matrices

Fundamental Numerical Methods for Electrical Engineering

Lecture 18 Classical Iterative Methods

= V I = Bus Admittance Matrix. Chapter 6: Power Flow. Constructing Ybus. Example. Network Solution. Triangular factorization. Let

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING Dundigal, Hyderabad MECHANICAL ENGINEERING TUTORIAL QUESTION BANK

Chapter 2. Solving Systems of Equations. 2.1 Gaussian elimination

Linear Equation Systems Direct Methods

Transcription:

UNIT II SOLUTION OF NON-LINEAR AND SIMULTANEOUS LINEAR EQUATION. If g x is continuous in a, b, then under what condition the iterative method x = g x has a unique solution in a, b? g x < in a, b. State the iterative formula for Regula Falsi method to solve f x =. The iteration formula to find the root of the equation f x =. which lies between x = a and x = b is x =. Explain Regula Falsi method of getting a root. a f b b f(a) f b f(a). Find two numbers a and b such that f a and f(b) are of opposite signs. Then a root lies between a and b.. The first approximation to the root is given by x = a f b b f(a) f b f(a). If f x and f(a) are opposite signs, then the actual root lies between x and a. Now replacing b by x and keeping a as it is we get the closer approximation x to the actual root. 4. This procedure is repeated till the root is found to the desired degree of accuracy. 4. How to reduce the number of iterations while finding the root of an equation by Regula Falsi method. The number of iterations to get a good approximation to the real root can be reduced, if we start with a smaller interval for the root. 5. What is the order of convergence of Newton- Raphson method if the multiplicity of the root is one. The order of convergence of Newton-Raphson method is 6. What is the rate of convergence in Newton-Raphson method? The rate of convergence in Newton-Raphson method is. 7. What is the criterion for convergence of Newton- Raphson method?.

The Criterion for convergence of Newton- Raphson -method is f x f x < f x in te interval considered. 8. Write the iterative formula for Newton- Raphson method. The Newton- Raphson formula is + = f f 9. What is the condition of convergence of a fixed point iteration method? Let f x = be the given equation whose actual root is r. The equation f x = be written as x = g x. Let I be the interval containing the root x = r. If g x < for all x in I, then the sequence of approximations x, x, x,. will converge to r, if the initial starting value x is chosen in I.. If g x is continuous in a, b, then under what condition the iterative method x = g x has a unique solution in a, b? g x < in a, b. What is the order of convergence of fixed point iteration method. The order of convergence of Newton-Raphson method is.. In what form is the coefficient matrix transformed into when A X = B is solved by Gauss elimination method? Upper triangular matrix.. In what form is the coefficient matrix transformed into when A X = B is solved by Gauss Jordan method? Diagonal matrix. 4. Explain briefly Gauss Jordan iteration to solve simultaneous equation? Consider the system of equations A X = B. If A is a square matrix the given system reduces to a a a nn x x = b b b n This system is reduces to the following n equations. a x = b, a x = b, a nn = b n x = b a, x = b a, = b n a nn

The method of obtaining the solution of the system of equations by reducing the matrix A to diagonal matrix is known as Gauss Jordan elimination method. 5. For solving a linear system, compare Gauss - elimination method and Gauss Jordan method. Gauss - elimination method Coefficient matrix transformed into upper triangular matrix Gauss Jordan method Coefficient matrix transformed into diagonal matrix Direct method Direct method We obtain the solution by Backward substitution method No need of Backward substitution method 6. State the principle used in Gauss Jordan method. Coefficient matrix transformed into upper triangular matrix 7. Write the sufficient condition for Gauss - Siedal method to converge. The coefficient of matrix should be diagonally dominant. a > b + c, b > a + c, c > a + b 8. State the sufficient condition for Gauss - Jacobi method to converge. The coefficient of matrix should be diagonally dominant. a > b + c, b > a + c, c > a + b 9. Give two indirect methods to solve a system of linear equations. (). Gauss Jacobi method (). Gauss Siedal method. Compare Gauss Jacobi method and Gauss Siedal method Gauss Jacobi method Convergence rate is slow Indirect method Indirect method Condition for the convergence is the coefficient matrix is diagonally dominant Gauss Siedal method The rate of convergence of Gauss Siedal method is roughly twice that of Gauss - Jacobi Condition for the convergence is the coefficient matrix is diagonally dominant

. Find the first approximation to the root lying between and of x + x = by Newton s method. f x = x + x and f x = x + x = f x f x =... Find an iteration formula for finding the square root of N by Newton method. f x = x N and f x = x + = f f N = x n + N, n =,,,. How do you express the equation x + x = for the positive root by iteration method? x + x = x x + = x x + = x = x + x = = g x x + 4. Can we write iteration method to find the root of the equation x cos x = in, π?. x cos x = x = + cos x x = + cos x = φ x φ x = + cos x φ x = sin x φ = sin < and φ π = sin π =.5 <. Hence φ x = sin x < for all I =, π. Therefore we can use iteration method. 5. Is the system of equations x + 9y z =, 4x + y + z =, 4x y + z = Diagonally dominant? If not make it diagonally dominant. Let x + 9y z =, 4x + y + z =, 4x y + z = a > b + c, b > a + c and c > a + b 4

Hence the given system is not diagonally dominant. Hence we rearrange the system as follows 4x y + z = x + 9y z =, 4x + y + z = 6. Write Newton s formula for finding cube root of N. x N = f x = x N and f x = x By newton smetod, we ave 7. Write Newton s formula for finding reciprocal of a positive N. + = N, n =,, N = f x = N and x x f x = x By newton x N smetod + = n = x n N, n =,, 8. What is the basic principle involved in triangularisation method? Ans. The method of triangularisation is based on the fact that the coefficient matrix can be expressed as the product of a unit lower triangular matrix and an upper triangular matrix. 5