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Computational Methods In Nonlinear Analysis: Efficient Algorithms, Fixed Point Theory And Applications [Kõva köide]

(Poitiers Univ, France), (Cameron Univ, Usa)
  • Formaat: Hardback, 592 pages
  • Ilmumisaeg: 30-Aug-2013
  • Kirjastus: World Scientific Publishing Co Pte Ltd
  • ISBN-10: 9814405825
  • ISBN-13: 9789814405829
  • Formaat: Hardback, 592 pages
  • Ilmumisaeg: 30-Aug-2013
  • Kirjastus: World Scientific Publishing Co Pte Ltd
  • ISBN-10: 9814405825
  • ISBN-13: 9789814405829
The field of computational sciences has seen a considerable development in mathematics, engineering sciences, and economic equilibrium theory. Researchers in this field are faced with the problem of solving a variety of equations or variational inequalities. We note that in computational sciences, the practice of numerical analysis for finding such solutions is essentially connected to variants of Newton's method. The efficient computational methods for finding the solutions of fixed points problems, nonlinear equations and variational inclusions are the first goal of the present book. The second goal is the applications of these methods in nonlinear problems and the connection with fixed point theory.This book is intended for researchers in computational sciences, and as a reference book for an advanced computational methods in nonlinear analysis. We collect the recent results on the convergence analysis of numerical algorithms in both finite-dimensional and infinite-dimensional spaces, and present several applications and connections with fixed point theory. The book contains abundant and updated bibliography, and provides comparison between various investigations made in recent years in the field of computational nonlinear analysis.
Preface vii
1 Newton's Methods
1(88)
1.1 Convergence under Lipschitz Conditions
1(23)
1.2 Convergence under Generalized Lipschitz Conditions
24(20)
1.3 Convergence without Lipschitz Conditions
44(13)
1.4 Convex Majorants
57(12)
1.5 Nondiscrete Induction
69(17)
1.6 Exercises
86(3)
2 Special Conditions for Newton's Method
89(36)
2.1 ω*-Convergence
89(9)
2.2 Regular Smoothness
98(10)
2.3 Smale's α-Theory
108(13)
2.4 Exercises
121(4)
3 Newton's Method on Special Spaces
125(94)
3.1 Lie Groups
125(19)
3.2 Hilbert Space
144(7)
3.3 Convergence Structure
151(13)
3.4 Riemannian Manifolds
164(18)
3.5 Newton-type Method on Riemannian Manifolds
182(20)
3.6 Traub-type Method on Riemannian Manifolds
202(15)
3.7 Exercises
217(2)
4 Secant Method
219(76)
4.1 Semi-local Convergence
219(12)
4.2 Secant-type Method and Nondiscrete Induction
231(10)
4.3 Efficient Secant-type Method
241(11)
4.4 Secant-like Method and Recurrent Functions
252(15)
4.5 Directional Secant-type Method
267(15)
4.6 A Unified Convergence Analysis
282(12)
4.7 Exercises
294(1)
5 Gauss-Newton Method
295(40)
5.1 Regularized Gauss-Newton Method
295(3)
5.2 Convex Composite Optimization
298(17)
5.3 Proximal Gauss-Newton Method
315(11)
5.4 Inexact Method and Majorant Conditions
326(8)
5.5 Exercises
334(1)
6 Halley's Method
335(28)
6.1 Semi-local Convergence
335(8)
6.2 Local Convergence
343(7)
6.3 Traub-type Multipoint Method
350(11)
6.4 Exercises
361(2)
7 Chebyshev's Method
363(38)
7.1 Directional Methods
363(13)
7.2 Chebyshev-Secant Methods
376(7)
7.3 Majorizing Sequences for Chebyshev's Method
383(13)
7.4 Exercises
396(5)
8 Broyden's Method
401(14)
8.1 Semi-local Convergence
401(13)
8.2 Exercises
414(1)
9 Newton-like Methods
415(86)
9.1 Modified Newton Method and Multiple Zeros
415(12)
9.2 Weak Convergence Conditions
427(7)
9.3 Local Convergence for Newton-type Method
434(6)
9.4 Two-step Newton-like Method
440(9)
9.5 A Unifying Semi-local Convergence
449(15)
9.6 High Order Traub-type Methods
464(13)
9.7 Relaxed Newton's Method
477(20)
9.8 Exercises
497(4)
10 Newton-Tikhonov Method for Ill-posed Problems
501(52)
10.1 Newton-Tikhonov Method in Hilbert Space
501(14)
10.2 Two-step Newton-Tikhonov Method in Hilbert Space
515(15)
10.3 Regularization Methods
530(20)
10.4 Exercises
550(3)
Bibliography 553(20)
Index 573