Errors in Numerical Computations Introduction Preliminary Mathematical Theorems Approximate Numbers and Significant Figures Rounding Off Numbers Truncation Errors Floating Point Representation of Numbers Propagation of Errors General Formula for Errors Loss of Significance Errors Numerical Stability, Condition Number, and Convergence Brief Idea of Convergence ----Numerical Solutions of Algebraic and Transcendental EquationsIntroduction Basic Concepts and Definitions Initial ApproximationIterative Methods Generalized Newtons Method Graeffes Root Squaring Method for Algebraic Equations ----Interpolation Introduction Polynomial Interpolation ----Numerical Differentiation Introduction Errors in Computation of Derivatives Numerical Differentiation for Equispaced Nodes Numerical Differentiation for Unequally Spaced Nodes Richardson Extrapolation ----Numerical Integration Introduction Numerical Integration from Lagranges Interpolation NewtonCotes Formula for Numerical Integration (Closed Type) NewtonCotes Quadrature Formula (Open Type) Numerical Integration Formula from Newtons Forward Interpolation Formula Richardson Extrapolation Romberg Integration Gauss Quadrature Formula Gaussian Quadrature: Determination of Nodes and Weights through Orthogonal Polynomials Lobatto Quadrature Method Double Integration Bernoulli Polynomials and Bernoulli NumbersEulerMaclaurin Formula ----Numerical Solution of System of Linear Algebraic Equations Introduction Vector and Matrix Norm Direct MethodsIterative Method Convergent Iteration Matrices Convergence of Iterative Methods Inversion of a Matrix by the Gaussian Method Ill-Conditioned Systems Thomas Algorithm ----Numerical Solutions of Ordinary Differential Equations Introduction Single-Step Methods Multistep Methods System of Ordinary Differential Equations of First Order Differential Equations of Higher Order Boundary Value Problems Stability of an Initial Value Problem Stiff Differential Equations A-Stability and L-Stability----Matrix Eigenvalue Problem Introduction Inclusion of Eigenvalues Householders Method The QR Method Power Method Inverse Power Method Jacobis Method Givens Method ----Approximation of Functions Introduction Least Square Curve Fitting Least Squares Approximation Orthogonal Polynomials The Minimax Polynomial Approximation B-Splines Pad Approximation ----Numerical Solutions of Partial Differential Equations Introduction Classification of PDEs of Second Order Types of Boundary Conditions and Problems Finite-Difference Approximations to Partial Derivatives Parabolic PDEs Hyperbolic PDEs Elliptic PDEs Alternating Direction Implicit Method Stability Analysis of the Numerical Schemes ----An Introduction to the Finite Element Method Introduction Piecewise Linear Basis Functions The RayleighRitz Method The Galerkin Method ----Bibliography --Answers --Index ----Exercises appear at the end of each chapter.

Numerical Analysis with Algorithms and Programming is the first comprehensive textbook to provide detailed coverage of numerical methods, their algorithms, and corresponding computer programs. It presents many techniques for the efficient numerical solution of problems in science and engineering. Along with numerous worked-out examples, end-of-chapter exercises, and Mathematica® programs, the book includes the standard algorithms for numerical computation: Root finding for nonlinear equations Interpolation and approximation of functions by simpler computational building blocks, such as polynomials and splines The solution of systems of linear equations and triangularization. Approximation of functions and least square approximation. Numerical differentiation and divided differences, Numerical quadrature and integration, Numerical solutions of ordinary differential equations (ODEs) and boundary value problems, Numerical solution of partial differential equations (PDEs). The text develops students' understanding of the construction of numerical algorithms and the applicability of the methods. By thoroughly studying the algorithms, students will discover how various methods provide accuracy, efficiency, scalability, and stability for large-scale systems.

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