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E-raamat: Computational Functional Analysis

(Lawrence Technological University, USA), (Ohio State University)
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  • Ilmumisaeg: 01-Jun-2007
  • Kirjastus: Horwood Publishing Ltd
  • Keel: eng
  • ISBN-13: 9780857099433
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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 01-Jun-2007
  • Kirjastus: Horwood Publishing Ltd
  • Keel: eng
  • ISBN-13: 9780857099433
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Written for senior undergraduate and first-year graduate students, this introduces functional analysis tools and prepares readers for further studies in numerical mathematics of mathematical modeling. Moore (computer and information science, Ohio State U.) and Cloud (electrical and computer engineering, Lawrence Technological U.) offer more than 100 exercise while covering linear spaces, topological spaces, metric spaces, normed linear spaces and Banach spaces, inner product spaces and Hilbert spaces, linear functionals, types of convergence in function space, reproducing kernel Hilbert spaces, order relations in function spaces, operators in function space, completely continuous operators, approximation methods for linear operator equations, interval methods for operator equations, contraction mappings and iterative methods, Newton's method in Banach spaces, variants of Newton's methods, and homotopy and continuation methods and a hybrid method for a free-boundary problem. Distributed by ISBS. Annotation ©2007 Book News, Inc., Portland, OR (booknews.com)

This course text fills a gap for first-year graduate-level students reading applied functional analysis or advanced engineering analysis and modern control theory. Containing 100 problem-exercises, answers, and tutorial hints, the first edition is often cited as a standard reference. Making a unique contribution to numerical analysis for operator equations, it introduces interval analysis into the mainstream of computational functional analysis, and discusses the elegant techniques for reproducing Kernel Hilbert spaces. There is discussion of a successful ‘‘hybrid’’ method for difficult real-life problems, with a balance between coverage of linear and non-linear operator equations. The authors' successful teaching philosophy: ‘‘We learn by doing’’ is reflected throughout the book.

Arvustused

A stimulating and challenging introduction, (Review of the first edition) SIAM Review, USA, (William W. Hager, Pennsylvania State University). A very readable introduction, excellent., The Mathematical Gazette

Preface vii
Notation ix
Introduction
1(2)
Linear Spaces
3(4)
linear manifolds
isomorphic spaces
Cartesian products
equivalence classes
factor spaces
Topological Spaces
7(4)
convergent sequences
compactness
relative compactness
sequential compactness: continuous functions
inverse mappings
homeomorphisms
Metric Spaces
11(4)
metrics
isometrics
Cauchy sequences
completeness
dense subsets
separable metric spaces
completion of a metric space
Normed Linear Spaces and Banach Spaces
15(4)
norms
bounded subsets
Banach spaces
subspaces
Inner Product Spaces and Hilbert Spaces
19(9)
Inner products
Cauchy--Schwarz inequality
orthogonality
En and l2
Hilbert spaces
l2[ a, b] and l2
unit vectors
orthonormal sequences
complete orthonormal sequences
separable Hilbert spaces
span of a subset
orthogonal projections
orthogonal complements
orthonormal bases
Parseval's identity and relation
Fourier coefficients
the Gram-Schmidt process
Linear Functionals
28(4)
functionals
linear functionals
bounded linear functionals
evaluation functionals
finite sums
definite integrals
inner products
the Riesz representation theorem
null spaces
norms
the Hahn--Banach theorem
unbounded functionals
conjugate (dual) spaces
Types of Convergence in Function Spaces
32(3)
strong convergence
weak convergence
pointwise convergence
uniform convergence
star convergence
weak-star convergence
Reproducing Kernel Hilbert Spaces
35(7)
reproducing kernels
orthogonal projection
interpolation
approximate integration
Order Relations in Function Spaces
42(7)
reflexive partial orderings
intervals
interval valued mappings into reflexively partially ordered sets
lattices
complete lattices
order convergence
united extensions
subset property of arbitrary mappings
the Knaster--Tarski theorem
fixed points of arbitrary mappings
line segments in linear spaces
convex sets
convex mappings
Operators in Function Spaces
49(11)
Operators
linear operators
nonlinear operators
null spaces
non-singular linear operators
continuous linear operators
bounded linear operators
Neumann series and solution of certain linear operator equations
adjoint operators
selfadjoint operators
matrix representations of bounded linear operators on separable Hilbert spaces
the space L(H, H) of bounded linear operators
types of convergence in L(H, H)
Jacobi iteration and Picard iteration
linear initial value problems
Completely Continuous (Compact) Operators
60(8)
completely continuous operators
Hilbert--Schmidt integral operators
projection operators into finite dimensional subspaces
spectral theory of completely continuous operators
eigenfunction expansions
Galerkin's method
completely continuous operators in Banach spaces
the Fredholm alternative
Approximation Methods for Linear Operator Equations
68(15)
finite basis methods
finite difference methods
separation of variables and eigenfunction expansions for the diffusion equation
rates of convergence
Galerkin's method in Hilbert spaces
collocation methods
finite difference methods
Fredholm integral equations
the Nystrom method
Interval Methods for Operator Equations
83(11)
interval arithmetic
interval integration
interval operators
inclusion isotonicity
nonlinear operator equations with data perturbations
Contraction Mappings and Iterative Methods
94(8)
fixed point problems
contraction mappings
initial value problems
two-point boundary value problems
Frechet Derivatives
102(14)
Frechet differentiable operators
locally linear operators
the Frechet derivative
the Gateaux derivative
higher Frechet derivatives
the Taylor theorem in Banach spaces
Newton's Method in Banach Spaces
116(15)
Newton's iterative method for nonlinear operator equations
local convergence
the error squaring property
the Kantorovich theorem
computational verification of convergence conditions using interval analysis
interval versions of Newton's method
Variants of Newton's Method
131(7)
a general theorem
Ostrowski's theorem
Newton's method
the simplified Newton method
the SOR-Newton method (generalized Newton method)
a Gauss--Seidel modification
Homotopy and Continuation Methods
138(8)
homotopies
successive perturbation methods
continuation methods
curve of zeros
discrete continuation
Davidenko's method
computational aspects
A Hybrid Method for a Free Boundary Problem
146(14)
Hints for Selected Exercises 160(13)
Further Reading 173(4)
Index 177


Ramon E. Moore, Ohio State University, USA. Michael J. Cloud, Lawrence Technological University, USA.