Vector space

About: Vector space is a research topic. Over the lifetime, 7664 publications have been published within this topic receiving 167821 citations. The topic is also known as: linear space.

Perturbation theory for linear operators

Abstract: "The monograph by T Kato is an excellent textbook in the theory of linear operators in Banach and Hilbert spaces It is a thoroughly worthwhile reference work both for graduate students in functional analysis as well as for researchers in perturbation, spectral, and scattering theory In chapters 1, 3, 5 operators in finite-dimensional vector spaces, Banach spaces and Hilbert spaces are introduced Stability and perturbation theory are studied in finite-dimensional spaces (chapter 2) and in Banach spaces (chapter 4) Sesquilinear forms in Hilbert spaces are considered in detail (chapter 6), analytic and asymptotic perturbation theory is described (chapter 7 and 8) The fundamentals of semigroup theory are given in chapter 9 The supplementary notes appearing in the second edition of the book gave mainly additional information concerning scattering theory described in chapter 10 The first edition is now 30 years old The revised edition is 20 years old Nevertheless it is a standard textbook for the theory of linear operators It is user-friendly in the sense that any sought after definitions, theorems or proofs may be easily located In the last two decades much progress has been made in understanding some of the topics dealt with in the book, for instance in semigroup and scattering theory However the book has such a high didactical and scientific standard that I can recomment it for any mathematician or physicist interested in this field Zentralblatt MATH, 836

Interpolation Spaces: An Introduction

Abstract: 1. Some Classical Theorems.- 1.1. The Riesz-Thorin Theorem.- 1.2. Applications of the Riesz-Thorin Theorem.- 1.3. The Marcinkiewicz Theorem.- 1.4. An Application of the Marcinkiewicz Theorem.- 1.5. Two Classical Approximation Results.- 1.6. Exercises.- 1.7. Notes and Comment.- 2. General Properties of Interpolation Spaces.- 2.1. Categories and Functors.- 2.2. Normed Vector Spaces.- 2.3. Couples of Spaces.- 2.4. Definition of Interpolation Spaces.- 2.5. The Aronszajn-Gagliardo Theorem.- 2.6. A Necessary Condition for Interpolation.- 2.7. A Duality Theorem.- 2.8. Exercises.- 2.9. Notes and Comment.- 3. The Real Interpolation Method.- 3.1. The K-Method.- 3.2. The J-Method.- 3.3. The Equivalence Theorem.- 3.4. Simple Properties of ??, q.- 3.5. The Reiteration Theorem.- 3.6. A Formula for the K-Functional.- 3.7. The Duality Theorem.- 3.8. A Compactness Theorem.- 3.9. An Extremal Property of the Real Method.- 3.10. Quasi-Normed Abelian Groups.- 3.11. The Real Interpolation Method for Quasi-Normed Abelian Groups.- 3.12. Some Other Equivalent Real Interpolation Methods.- 3.13. Exercises.- 3.14. Notes and Comment.- 4. The Complex Interpolation Method.- 4.1. Definition of the Complex Method.- 4.2. Simple Properties of ?[?].- 4.3. The Equivalence Theorem.- 4.4. Multilinear Interpolation.- 4.5. The Duality Theorem.- 4.6. The Reiteration Theorem.- 4.7. On the Connection with the Real Method.- 4.8. Exercises.- 4.9. Notes and Comment.- 5. Interpolation of Lp-Spaces.- 5.1. Interpolation of Lp-Spaces: the Complex Method.- 5.2. Interpolation of Lp-Spaces: the Real Method.- 5.3. Interpolation of Lorentz Spaces.- 5.4. Interpolation of Lp-Spaces with Change of Measure: p0 = p1.- 5.5. Interpolation of Lp-Spaces with Change of Measure: p0 ? p1.- 5.6. Interpolation of Lp-Spaces of Vector-Valued Sequences.- 5.7. Exercises.- 5.8. Notes and Comment.- 6. Interpolation of Sobolev and Besov Spaces.- 6.1. Fourier Multipliers.- 6.2. Definition of the Sobolev and Besov Spaces.- 6.3. The Homogeneous Sobolev and Besov Spaces.- 6.4. Interpolation of Sobolev and Besov Spaces.- 6.5. An Embedding Theorem.- 6.6. A Trace Theorem.- 6.7. Interpolation of Semi-Groups of Operators.- 6.8. Exercises.- 6.9. Notes and Comment.- 7. Applications to Approximation Theory.- 7.1. Approximation Spaces.- 7.2. Approximation of Functions.- 7.3. Approximation of Operators.- 7.4. Approximation by Difference Operators.- 7.5. Exercises.- 7.6. Notes and Comment.- References.- List of Symbols.

Recursive methods in economic dynamics

Abstract: I. THE RECURSIVE APPROACH 1. Introduction 2. An Overview 2.1 A Deterministic Model of Optimal Growth 2.2 A Stochastic Model of Optimal Growth 2.3 Competitive Equilibrium Growth 2.4 Conclusions and Plans II. DETERMINISTIC MODELS 3. Mathematical Preliminaries 3.1 Metric Spaces and Normed Vector Spaces 3.2 The Contraction Mapping Theorem 3.3 The Theorem of the Maximum 4. Dynamic Programming under Certainty 4.1 The Principle of Optimality 4.2 Bounded Returns 4.3 Constant Returns to Scale 4.4 Unbounded Returns 4.5 Euler Equations 5. Applications of Dynamic Programming under Certainty 5.1 The One-Sector Model of Optimal Growth 5.2 A "Cake-Eating" Problem 5.3 Optimal Growth with Linear Utility 5.4 Growth with Technical Progress 5.5 A Tree-Cutting Problem 5.6 Learning by Doing 5.7 Human Capital Accumulation 5.8 Growth with Human Capital 5.9 Investment with Convex Costs 5.10 Investment with Constant Returns 5.11 Recursive Preferences 5.12 Theory of the Consumer with Recursive Preferences 5.13 A Pareto Problem with Recursive Preferences 5.14 An (s, S) Inventory Problem 5.15 The Inventory Problem in Continuous Time 5.16 A Seller with Unknown Demand 5.17 A Consumption-Savings Problem 6. Deterministic Dynamics 6.1 One-Dimensional Examples 6.2 Global Stability: Liapounov Functions 6.3 Linear Systems and Linear Approximations 6.4 Euler Equations 6.5 Applications III. STOCHASTIC MODELS 7. Measure Theory and Integration 7.1 Measurable Spaces 7.2 Measures 7.3 Measurable Functions 7.4 Integration 7.5 Product Spaces 7.6 The Monotone Class Lemma

Infinite Dimensional Analysis: A Hitchhiker's Guide

Abstract: Odds and ends- Topology- Metrizable spaces- Measurability- Topological vector spaces- Normed spaces- Convexity- Riesz spaces- Banach lattices- Charges and measures- Integrals- Measures and topology- Lp-spaces- Riesz Representation Theorems- Probability measures- Spaces of sequences- Correspondences- Measurable correspondences- Markov transitions- Ergodicity

An Introduction to Γ-Convergence

Abstract: 1. The direct method in the calculus of variations.- 2. Minimum problems for integral functionals.- 3. Relaxation.- 4. ?-convergence and K-convergence.- 5. Comparison with pointwise convergence.- 6. Some properties of ?-limits.- 7. Convergence of minima and of minimizers.- 8. Sequential characterization of ?-limits.- 9. ?-convergence in metric spaces.- 10. The topology of ?-convergence.- 11. ?-convergence in topological vector spaces.- 12. Quadratic forms and linear operators.- 13. Convergence of resolvents and G-convergence.- 14. Increasing set functions.- 15. Lower semicontinuous increasing functionals.- 16. $$ \bar{\Gamma } $$-convergence of increasing set functional.- 17. The topology of $$ \bar{\Gamma } $$-convergence.- 18. The fundamental estimate.- 19. Local functionals and the fundamental estimate.- 20. Integral representation of ?-limits.- 21. Boundary conditions.- 22. G-convergence of elliptic operators.- 23. Translation invariant functional.- 24. Homogenization.- 25. Some examples in homogenization.- Guide to the literature.