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9780817642402

Structured Matrices and Polynomials

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  • ISBN13:

    9780817642402

  • ISBN10:

    0817642404

  • Format: Hardcover
  • Copyright: 2001-12-01
  • Publisher: Birkhauser

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Summary

Structured matrices serve as a natural bridge between the areas of algebraic computations with polynomials and numerical matrix computations, allowing cross-fertilization of both fields. This book covers most fundamental numerical and algebraic computations with Toeplitz, Hankel, Vandermonde, Cauchy, and other popular structured matrices. Throughout the computations, the matrices are represented by their compressed images, called displacements, enabling both a unified treatment of various matrix structures and dramatic saving of computer time and memory. The resulting superfast algorithms allow further dramatic parallel acceleration using FFT and fast sine and cosine transforms. Included are specific applications to other fields, in particular, superfast solutions to: various fundamental problems of computer algebra; the tangential Nevanlinna--Pick and matrix Nehari problems The primary intended readership for this work includes researchers, algorithm designers, and advanced graduate students in the fields of computations with structured matrices, computer algebra, and numerical rational interpolation. The book goes beyond research frontiers and, apart from very recent research articles, includes yet unpublished results. To serve a wider audience, the presentation unfolds systematically and is written in a user-friendly engaging style. Only some preliminary knowledge of the fundamentals of linear algebra is required. This makes the material accessible to graduate students and new researchers who wish to study the rapidly exploding area of computations with structured matrices and polynomials. Examples, tables, figures, exercises, extensive bibliography, and index lend this text to classroom use or self-study.

Table of Contents

Preface ix
Glossary xix
List of Tables
xxiii
List of Figures
xxv
Computations with Structured Matrices. Introduction
1(22)
Application areas, our subjects and objectives
1(2)
Four features of structured matrices
3(1)
Displacements (some history, definitions and examples)
4(3)
Compress, Operate, Decompress
7(3)
Basic operations with compressed structured matrices
10(2)
Two classes of superfast algorithms. The case of Toeplitz-like matrices
12(1)
Unified algorithms and algorithmic transformations
13(2)
Numerical and algebraic versions of structured matrix algorithms. Flops and ops
15(3)
Numerical implementation
15(2)
Algebraic implementation
17(1)
Unification and separation of numerical and algebraic versions of algorithms
17(1)
Computational complexity estimates
17(1)
Limitations of the unification
18(1)
Organization of the book
19(1)
Notes
19(2)
Exercises
21(2)
Toeplitz/Hankel Matrix Structure and Polynomial Computations
23(50)
Definitions and preliminaries
23(2)
Fast Fourier transform (polynomial version)
25(1)
Fast Fourier transform (matrix version)
26(1)
Polynomial multiplication (with extensions)
27(3)
Polynomial division and triangular Toeplitz matrix inversion
30(3)
The algebra of f-circulant matrices. Diagonalizations by DFT's
33(3)
Algebra of polynomials modulo a polynomial and the Frobenius matrix algebra
36(4)
Polynomial gcd and the (Extended) Euclidean Algorithm
40(6)
Applications and extensions of the EEA: modular division, rational function reconstruction, Pade approximation, and linear recurrence span
46(4)
Matrix algorithms for rational interpolation and the EEA
50(2)
Matrix approach to Pade approximation
52(3)
Conclusion
55(1)
Notes
56(1)
Exercises
57(4)
Appendix. Pseudocodes
61(12)
Matrix Structures of Vandermonde and Cauchy Types and Polynomial and Rational Computations
73(44)
Multipoint polynomial evaluation
73(3)
Modular reduction and other extensions
76(2)
Lagrange polynomial interpolation
78(2)
Polynomial interpolation (matrix method), transposed Vandermonde matrices, and composition of polynomials
80(2)
Chinese remainder algorithm, polynomial and rational Hermite interpolation, and decomposition into partial fractions
82(6)
Cauchy matrix computations. Polynomial and rational interpolation and multipoint evaluation
88(5)
Loss (erasure)-resilient encoding/decoding and structured matrices
93(3)
Nevanlinna-Pick interpolation problems
96(4)
Matrix Nehari Problem
100(1)
Sparse multivariate polynomial interpolation
101(2)
Diagonalization of Matrix Algebras. Polynomial Vandermonde Matrices and Discrete Sine and Cosine transforms
103(5)
Conclusion
108(1)
Notes
109(4)
Exercises
113(4)
Structured Matrices and Displacement Operators
117(38)
Some definitions and basic results
118(2)
Displacements of basic structured matrices
120(2)
Inversion of the displacement operators
122(3)
Compressed bilinear expressions for structured matrices
125(9)
Partly regular displacement operators
134(3)
Compression of a generator
137(4)
SVD-based compression of a generator in numerical computations with finite precision
137(2)
Elimination based compression of a generator in computations in an abstract field
139(2)
Structured matrix multiplication
141(3)
Algorithm design based on multiplicative transformation of operator matrix pairs
144(3)
Algorithm design based on similarity transformations of operator matrices
147(1)
Conclusion
148(1)
Notes
149(1)
Exercises
150(5)
Unified Divide-and-Conquer Algorithm
155(22)
Introduction. Our subject and results
155(1)
Complete recursive triangular factorization (CRTF) of general matrices
156(3)
Compressed computation of the CRTF of structured matrices
159(2)
Simplified compression of Schur complements
161(1)
Regularization via symmetrization
162(2)
Regularization via multiplicative transformation with randomization
164(3)
Randomization for structured matrices
167(1)
Applications to computer algebra, algebraic decoding, and numerical rational computations
168(2)
Conclusion
170(1)
Notes
170(2)
Exercises
172(5)
Newton-Structured Numerical Iteration
177(42)
Some definitions and preliminaries
178(1)
Newton's iteration for root-finding and matrix inversion
179(2)
Newton-Structured Iteration
181(1)
Compression of the displacements by the truncation of their smallest singular values
182(2)
Compression of displacement generators of approximate inverses by substitution
184(2)
Bounds on the norms of the inverse operator
186(3)
Introductory comments
186(1)
Bounds via powering the operator matrices
187(1)
The spectral approach
187(1)
The bilinear expression approach
188(1)
Estimation using the Frobenius norm
188(1)
Initialization, analysis, and modifications of Newton's iteration for a general matrix
189(4)
How much should we compress the displacements of the computed approximations?
193(2)
Homotopic Newton's iteration
195(6)
An outline of the algorithms
195(1)
Symmetrization of the input matrix
196(1)
Initialization of a homotopic process for the inversion of general and structured matrices
196(2)
The choice of step sizes for a homotopic process. Reduction to the choice of tolerance values
198(1)
The choice of tolerance values
199(1)
Variations and parallel implementation of the Newton-Structured Iteration
199(2)
Newton's iteration for a singular input matrix
201(1)
Numerical experiments with Toeplitz matrices
202(2)
Conclusion
204(10)
Notes
214(1)
Exercises
215(4)
Newton Algebraic Iteration and Newton-Structured Algebraic Iteration
219(22)
Some introductory remarks
219(1)
Newton's algebraic iteration: generic algorithm
220(3)
Specific examples of Newton's algebraic iteration
223(3)
Newton's algebraic iteration for the inversion of general matrices
226(1)
Newton and Newton-Structured Algebraic Iterations for characteristic polynomials and the Krylov spaces
227(2)
Extensions of Krylov space computation
229(1)
Inversion of general integer matrices and solution of general integer linear systems
230(2)
Sequences of primes, random primes, and non-singularity of a matrix
232(1)
Inversion of structured integer matrices
233(3)
Conclusion
236(1)
Notes
236(1)
Exercises
237(4)
Conclusion 241(2)
Bibliography 243(28)
Index 271

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