David Eric Edmunds

Bio: David Eric Edmunds is an academic researcher from University of Sussex. The author has contributed to research in topics: Function space & Sobolev space. The author has an hindex of 8, co-authored 18 publications receiving 2614 citations. Previous affiliations of David Eric Edmunds include King's College London.

Spectral theory and differential operators

Abstract: Linear operations in Banach spaces Entropy numbers, s-numbers, and eigenvalues Unbounded linear operators Sesquilinear forms in Hilbert spaces Sobolev spaces Generalized Dirichlet and Neumann boundary-value problems Second-order differential operators on arbitrary open sets Capacity and compactness criteria Essential spectra Essential spectra of general second-order differential operators Global and asymptotic estimates for the eigen-values of - + q when q is real. Estimates for the singular values of - + q when 1 is complete Bibliography Notation index Subject index

Function spaces, entropy numbers, differential operators

Abstract: 1. The abstract background 2. Function spaces 3. Entropy and approximation numbers of embeddings 4. Weighted function spaces and entropy numbers 5. Elliptic operators Bibliography.

Hardy Operators, Function Spaces and Embeddings

Abstract: 1 Preliminaries.- 2 Hardy-type Operators.- 3 Banach function spaces.- 4 Poincare and Hardy inequalities.- 5 Generalised ridged domains.- 6 Approximation numbers of Sobolev embeddings.- References.- Author Index.- Notation Index.

Bounded and compact integral operators

Abstract: Preface. Acknowledgments. Basic notation. 1. Hardy-type operators. 2. Fractional integrals on the line. 3. One-sided maximal functions. 4. Ball fractional integrals. 5. Potentials on RN. 6. Fractional integrals on measure spaces. 7. Singular numbers. 8. Singular integrals. 9. Multipliers of Fourier transforms. 10. Problems. References. Index.

Eigenvalues, Embeddings and Generalised Trigonometric Functions

Abstract: 1 Basic material.- 2 Trigonometric generalisations.- 3 The Laplacian and some natural variants.- 4 Hardy operators.- 5 s-Numbers and generalised trigonometric functions.- 6 Estimates of s-numbers of weighted Hardy operators.- 7 More refined estimates.- 8 A non-linear integral system.- 9 Hardy operators on variable exponent spaces

On the mathematical foundations of learning

Abstract: (1) A main theme of this report is the relationship of approximation to learning and the primary role of sampling (inductive inference). We try to emphasize relations of the theory of learning to the mainstream of mathematics. In particular, there are large roles for probability theory, for algorithms such as least squares, and for tools and ideas from linear algebra and linear analysis. An advantage of doing this is that communication is facilitated and the power of core mathematics is more easily brought to bear. We illustrate what we mean by learning theory by giving some instances. (a) The understanding of language acquisition by children or the emergence of languages in early human cultures. (b) In Manufacturing Engineering, the design of a new wave of machines is anticipated which uses sensors to sample properties of objects before, during, and after treatment. The information gathered from these samples is to be analyzed by the machine to decide how to better deal with new input objects (see [43]). (c) Pattern recognition of objects ranging from handwritten letters of the alphabet to pictures of animals, to the human voice. Understanding the laws of learning plays a large role in disciplines such as (Cognitive) Psychology, Animal Behavior, Economic Decision Making, all branches of Engineering, Computer Science, and especially the study of human thought processes (how the brain works). Mathematics has already played a big role towards the goal of giving a universal foundation of studies in these disciplines. We mention as examples the theory of Neural Networks going back to McCulloch and Pitts [25] and Minsky and Papert [27], the PAC learning of Valiant [40], Statistical Learning Theory as developed by Vapnik [42], and the use of reproducing kernels as in [17] among many other mathematical developments. We are heavily indebted to these developments. Recent discussions with a number of mathematicians have also been helpful. In

The local regularity of solutions of degenerate elliptic equations

Abstract: (1982). The local regularity of solutions of degenerate elliptic equations. Communications in Partial Differential Equations: Vol. 7, No. 1, pp. 77-116.

Spectra and pseudospectra

Abstract: The five sections of these notes will one day be the first five chapters of a book, to appear some time after 2001.

Mathematical foundations of infinite-dimensional statistical models

Abstract: 1. Nonparametric statistical models 2. Gaussian processes 3. Empirical processes 4. Function spaces and approximation theory 5. Linear nonparametric estimators 6. The minimax paradigm 7. Likelihood-based procedures 8. Adaptive inference.

Mathematical Methods in Quantum Mechanics

Abstract: Quantum mechanics and the theory of operators on Hilbert space have been deeply linked since their beginnings in the early twentieth century States of a quantum system correspond to certain elements of the configuration space and observables correspond to certain operators on the space This book is a brief, but self-contained, introduction to the mathematical methods of quantum mechanics, with a view towards applications to Schrodinger operators Part 1 of the book is a concise introduction to the spectral theory of unbounded operators Only those topics that will be needed for later applications are covered The spectral theorem is a central topic in this approach and is introduced at an early stage Part 2 starts with the free Schrodinger equation and computes the free resolvent and time evolution Position, momentum, and angular momentum are discussed via algebraic methods Various mathematical methods are developed, which are then used to compute the spectrum of the hydrogen atom Further topics include the nondegeneracy of the ground state, spectra of atoms, and scattering theory This book serves as a self-contained introduction to spectral theory of unbounded operators in Hilbert space with full proofs and minimal prerequisites: Only a solid knowledge of advanced calculus and a one-semester introduction to complex analysis are required In particular, no functional analysis and no Lebesgue integration theory are assumed It develops the mathematical tools necessary to prove some key results in nonrelativistic quantum mechanics Mathematical Methods in Quantum Mechanics is intended for beginning graduate students in both mathematics and physics and provides a solid foundation for reading more advanced books and current research literature This new edition has additions and improvements throughout the book to make the presentation more student friendly