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020			_a0201308606 (alk. paper)
039		9	_a201402040115 _bVLOAD _c201007191129 _dmalmash _c200812230841 _dvenkatrajand _c200812211211 _dNoora _y200812211208 _zNoora
050	0	0	_aTA345 _b.R43 2000
100	1		_aRecktenwald, Gerald W., _d1958- _943965
245	1	0	_aNumerical Methods with MATLAB : _bImplementations and Applications / _cGerald W. Recktenwald.
260			_aUpper Saddle River, N.J. : _bPrentice Hall, _cc2000.
300			_axxviii, 786 p. : _bill. ; _c25 cm.
504			_aIncludes bibliographical references (p. 735-739) and index.
505			_aNOTE: Chapters 2-12 conclude with Summary.) 1. Introduction. Terminology. MATLAB Overview. Organization of the Book. Rating Systems for Exercises. I. MATLAB BASICS. 2. Interactive Computing with MATLAB. Running MATLAB. Matrices and Vectors. Additional Types of Variables. Managing the Interactive Environment. Plotting in MATLAB. 3. MATLAB Programming. Script m-Files. Function m-Files. Input and Output. Flow Control. Vectorization. Deus ex Machina. 4. Organizing and Debugging MATLAB Programs. Organizing and Documenting m-Files. Organizing a Numerical Solution. Debugging. II. NUMERICAL TECHNIQUES. 5. Unavoidable Errors in Computing. Digital Representation of Numbers. Finite Precision Arithmetic. Truncation Error of Algorithms. 6. Finding the Roots of f(x)=0. Preliminaries. Fixed-Point Iteration. Bisection. Newton's Method. The Secant Method. Hybrid Methods. Roots of Polynomials. 7. A Review of Linear Algebra. Vectors. Matrices. Mathematical Properties of Vectors and Matrices. Special Matrices. 8. Solving Systems of Equations. Basic Concepts. Gaussian Elimination. Limitations on Numerical Solutions to Ax = b. Factorization Methods. Nonlinear Systems of Equations. 9. Least-Squares Fitting of a Curve to Data. Fitting a Line to Data. Least-Squares Fit to a Linear Combination of Functions. Multivariate Linear Least-Squares Fitting. 10. Interpolation. Basic Ideas. Interpolating Polynomials of Arbitrary Degree. Piecewise Polynomial Interpolation. MATLAB's Built in Interpolation Functions. 11. Numerical Integration. Basic Ideas and Nomenclature. Newton-Cotes Rules. Gaussian Quadrature. Adaptive Quadrature. Improper Integrals and Other Complications. 12. Numerical Integration of Ordinary Differential Equations. Basic Ideas and Nomenclature. Euler's Method. Higher Order One-Step Methods. Adaptive Stepsize Algorithms. Coupled ODEs. Additional Topics. Bibliography. Appendix A: Eigenvalues and Eigensystems. Eigenvectors Map onto Themselves. Mathematica
520			_aDesigned to give undergraduate engineering students a practical and rigorous introduction to the fundamentals of numerical computation. This book is a thoroughly modern exposition of classic numerical methods using MATLAB. The fundamental theory of each method is briefly developed. Rather than providing a detailed numerical analysis, the behavior of the methods is exposed by carefully designed numerical experiments. The methods are then exercised on several nontrivial example problems from engineering practice. The material in each chapter is organized as a progression from the simple to the complex. This leads the student to an understanding of the sophisticated numerical methods that are part of MATLAB. An integral part of the book is the Numerical Methods with MATLAB (NMM) Toolbox, which provides 150 programs and over forty data sets. The NMM Toolbox is a library of numerical techniques implemented in structured and clearly written code.
650		0	_aEngineering mathematics _xData processing. _94466
650		0	_aNumerical analysis _xData processing. _93649
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999			_c20223 _d20223