Numerical AnalysisNumerical Analysis, designed to be used in a one-year course for students in engineering, science and mathematics, helps the student gain a deeper understanding of numerical analysis by highlighting the five major ideas of the discipline: Convergence, Complexity, Conditioning, Compression, and Orthogonality and connecting back to them throughout the text. Each chapter contains a Reality Check, an extended foray into a relevant application area that can be used as a springboard for individual or team projects. MATLAB is used throughout to demonstrate and implement numerical methods. |
Contents
Fundamentals | 4 |
Solving Equations | 25 |
Systems of Equations | 75 |
Copyright | |
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Common terms and phrases
Apply approximate solution backward error Bézier Bézier curve Bisection Method bits boundary conditions calculation Chapter Chebyshev coefficients column command compression Computer Problem condition number convergence correct decimal places cubic spline curve data points defined derivative differential equation digits Discrete Cosine Transform double precision eigenvalues eigenvectors entries Euler's Method evaluate example Exercise Find Finite Difference Method fixed point Fixed-Point Iteration floating point formula Fourier transform Gaussian elimination initial condition initial guess initial value problem input integral interpolating polynomial interval inverse least squares linear MATLAB MATLAB code matrix Monte Carlo multiplication Newton's Method nonlinear normal equations orthogonal plot Power Iteration Program QR algorithm quantization random numbers real numbers root Secant Method shown in Figure shows Simpson's Rule solve solver step size h subintervals Theorem Trapezoid Method truncation error variable vector Wi+1 y₁ zero