数值算法的精确性与稳定性（影印版）（第2版）

　　list of figures
　　list of tables
　　preface to second edition
　　preface to first edition
　　about the dedication
　　1 principles of finite precision computation
　　2 floating point arithmetic
　　3 basics
　　4 summation
　　5 polynomials
　　6 norms
　　7 perturbation theory for linear systems
　　8 triangular systems
　　9 lu factorization and linear equations
　　10 cholesky factorization
　　11 symmetric indefinite and skew-symmetric systems
　　12 iterative refinement
　　13 block lu factorization
　　14 matrix inversion
　　15 condition number estimation
　　16 the sylvester equation
　　17 stationary iterative methods
　　18 matrix powers
　　19 qr factorization
　　20 the least squares problem
　　21 underdetermined systems
　　22 vandermonde systems
　　23 fast matrix multiplication
　　24 the fast fourier transform and applications
　　25 nonlinear systems and newton's method
　　26 automatic error analysis
　　27 software issues in floating point arithmetic
　　28 a gallery of test matrices
　　a solutions to problems
　　b acquiring software
　　c program libraries
　　d the matrix computation toolbox
　　bibliography
　　name index
　　subject index
　　 

　　Nicholas J. Higham is Richardson Professor of Applied Mathematics at the University of Manchester, England. He is the author of more than 80 publications and is a member of the editorial boards of Foundations of Computational Mathematics, the IMA Journal of Numerical Analysis, Linear Algebra and Its Applications, and the SIAM Journal on Matrix Analysis and Applications.

　　accuracy and stability of numerical algorithms gives a thorough, up-to-date treatment of the behavior of numerical algorithms in finite precision arithmetic. it combines algorithmic derivations, perturbation theory, and rounding error analysis, all enlivened by historical perspective and informative quotations.
　　this second edition expands and updates the coverage of the first edition (1996) and includes numerous improvements to the original material. two new chapters treat symmetric indefinite systems and skew-symmetric systems, and nonlinear systems and newton's method. twelve new sections include coverage of additional error bounds for gaussian elimination, rank revealing lu factorizations, weighted and constrained least squares problems, and the fused multiply-add operation found on some modern computer architectures. although not designed specifically as a textbook, this new edition is a suitable reference for an advanced course. it can also be used by instructors at all levels as a supplementary text from which to draw examples, historical perspective, statements of results, and exercises.