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Best Approximation Method An Introduction Softcover reprint of the original 1st ed. 1987 [Pehme köide]

  • Formaat: Paperback / softback, 172 pages, kõrgus x laius: 244x170 mm, kaal: 335 g, XIV, 172 p., 1 Paperback / softback
  • Sari: Lecture Notes in Engineering 27
  • Ilmumisaeg: 31-Mar-1987
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540175725
  • ISBN-13: 9783540175728
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  • Formaat: Paperback / softback, 172 pages, kõrgus x laius: 244x170 mm, kaal: 335 g, XIV, 172 p., 1 Paperback / softback
  • Sari: Lecture Notes in Engineering 27
  • Ilmumisaeg: 31-Mar-1987
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540175725
  • ISBN-13: 9783540175728
Teised raamatud teemal:
The most commonly used numerical techniques in solving engineering and mathematical models are the Finite Element, Finite Difference, and Boundary Element Methods. As computer capabilities continue to impro':e in speed, memory size and access speed, and lower costs, the use of more accurate but computationally expensive numerical techniques will become attractive to the practicing engineer. This book presents an introduction to a new approximation method based on a generalized Fourier series expansion of a linear operator equation. Because many engineering problems such as the multi­ dimensional Laplace and Poisson equations, the diffusion equation, and many integral equations are linear operator equations, this new approximation technique will be of interest to practicing engineers. Because a generalized Fourier series is used to develop the approxi­ mator, a "best approximation" is achieved in the "least-squares" sense; hence the name, the Best Approximation Method. This book guides the reader through several mathematics topics which are pertinent to the development of the theory employed by the Best Approximation Method. Working spaces such as metric spaces and Banach spaces are explained in readable terms. Integration theory in the Lebesque sense is covered carefully. Because the generalized Fourier series utilizes Lebesque integration concepts, the integra­ tion theory is covered through the topic of converging sequences of functions with respect to measure, in the mean (Lp), almost uniformly IV and almost everywhere. Generalized Fourier theory and linear operator theory are treated in Chapters 3 and 4.

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Springer Book Archives
1. Work Spaces.- 1.1. Metric Spaces.- 1.2. Linear Spaces.- 1.3. Normed
Linear Spaces.- 1.4. Banach Spaces.-
2. Integration Theory.- 2.0.
Introduction.- 2.1. The Riemann and Lebesgue Integrals: Step and Simple
Functions.- 2.2. Lebesque Measure.- 2.3. Measurable Functions.- 2.4. The
Lebesgue Integral.- 2.5. Key Theorems in Integration Theory.- 2.6. Lp
Spaces.- 2.7. The Metric Space, Lp.- 2.8. Convergence of Sequences.- 2.9.
Capsulation.- 3: Hilbert Space and Generalized Fourier Series.- 3.0
Introduction.- 3.1. Inner Product and Hilbert Space (Finite Dimension
Spaces).- 3.2. Infinite Dimension Spaces.- 3.3. Approximations in L2(E).-
3.4. Vector Space Representation for Approximations: An Application.-
4.
Linear Operators.- 4.0. Introduction.- 4.1. The Derivative as a Linear
Operator.- 4.2. Linear Operators.- 4.3. Examples of Linear Operators in
Engineering.- 4.4. Linear Operator Norms.-
5. The Best Approximation Method.-
5.0. Introduction.- 5.1. An Inner Product for the Solution of Linear Operator
Equations.- 5.2. Orthonormalization Process.- 5.3. Generalized Fourier
Series.- 5.4. Approximation Error Evaluation.- 5.5. The Weighted Inner
Product.-
6. The Best Approximation Method: Applications.- 6.0.
Introduction.- 6.1. Sensitivity of Computational Results to Variation in the
Inner Product Weighting Factor.- 6.2. Solving Two-Dimensional Potential
Problems.- 6.3. Application to Other Linear Operators.- 6.4. Computer
Program: Two-Dimensional Potential Problems Using Real Variable Basis
Functions.-
7. Coupling the Best Approximation and Complex Variable Boundary
Element Methods.- 7.0. Introduction.- 7.1. The Complex Variable Boundary
Element Method.- 7.2. Mathematical Development.- 7.3. The CVBEM and W?.- 7.4.
The Space W?A.- 7.5. Applications.- 7.6. Computer Program:Two-Dimensional
Potential Problems Using Analytic Basis Functions (CVBEM).- References.-
Appendix A: Derivation of CVBEM Approximation Function.- Appendix B:
Convergence of CVBEM Approximator.