Wave propagation [[electronic resource] ] : from electrons to photonic crystals and left-handed materials / / Peter Markoš, Costa M. Soukoulis

• Record Nr.: UNINA9910456746003321
• Autore: Markoš Peter
• Pubbl/distr/stampa: Princeton, : Princeton University Press, 2008
• ISBN: 1-68015-901-1; 1-282-53177-8; 9786612531774; 1-4008-3567-4
• Edizione: [Course Book]
• Descrizione fisica: 1 online resource (367 p.)
• Altri autori (Persone): SoukoulisC. M
• Disciplina: 530.14/1; 530.141; 621.38131
• Soggetti: Electric waves; Electromagnetic waves - Mathematics; Matrices; Wave-motion, Theory of; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Frontmatter -- Contents -- Preface -- 1 Transfer Matrix -- 2 Rectangular Potentials -- 3 δ-Function Potential -- 4 Kronig-Penney Model -- 5 Tight Binding Model -- 6 Tight Binding Models of Crystals -- 7 Disordered Models -- 8 Numerical Solution of the Schrödinger Equation -- 9 Transmission and Reflection of Plane Electromagnetic Waves on an Interface -- 10 Transmission and Reflection Coefficients for a Slab -- 11 Surface Waves -- 12 Resonant Tunneling through Double-Layer Structures -- 13 Layered Electromagnetic Medium: Photonic Crystals -- 14 Effective Parameters -- 15 Wave Propagation in Nonlinear Structures -- 16 Left-Handed Materials -- Appendix A. Matrix Operations -- Appendix B. Summary of Electrodynamics Formulas -- Bibliography -- Index
• Sommario/riassunto: This textbook offers the first unified treatment of wave propagation in ; electronic and electromagnetic systems and introduces readers to the essentials of the transfer matrix method, a powerful analytical tool that can be used to model and study an array of problems pertaining to wave propagation in electrons and photons. It is aimed at graduate and advanced undergraduate students in physics, materials science, electrical and computer engineering, and mathematics, and is ideal for researchers in photonic crystals, negative index materials, left-handed materials, plasmonics, nonlinear effects, and optics. Peter Markos and Costas Soukoulis begin by establishing the analogy between wave propagation in electronic systems and electromagnetic media and then show how the transfer matrix can be easily applied to any type of wave propagation, such as electromagnetic, acoustic, and elastic waves. The transfer matrix approach of the tight-binding model allows readers to understand its implementation quickly and all the concepts of solid-state physics are clearly introduced. Markos and Soukoulis then build the discussion of such topics as random systems and localized and delocalized modes around the transfer matrix, bringing remarkable clarity to the subject. Total internal reflection, Brewster angles, evanescent waves, surface waves, and resonant tunneling in left-handed materials are introduced and treated in detail, as are important new developments like photonic crystals, negative index materials, and surface plasmons. Problem sets aid students working through the subject for the first time.

Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier

• Record Nr.: UNINA9910830737403321
• Pubbl/distr/stampa: London, : ISTE; Hoboken, NJ, : John Wiley, c2008
• ISBN: 1-282-16506-2; 9786612165061; 0-470-61119-7; 0-470-39382-3
• Descrizione fisica: 1 online resource (383 p.)
• Collana: Digital signal and image processing series. ; ; v.35
• Altri autori (Persone): IdierJérôme
• Disciplina: 515/.357; 519.542
• Soggetti: Inverse problems (Differential equations); Bayesian statistical decision theory
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Bayesian Approach to Inverse Problems; Table of Contents; Introduction; Part I. Fundamental Problems and Tools; Chapter 1. Inverse Problems, Ill-posed Problems; 1.1. Introduction; 1.2. Basic example; 1.3. Ill-posed problem; 1.3.1. Case of discrete data; 1.3.2. Continuous case; 1.4. Generalized inversion; 1.4.1. Pseudo-solutions; 1.4.2. Generalized solutions; 1.4.3. Example; 1.5. Discretization and conditioning; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Main Approaches to the Regularization of Ill-posed Problems; 2.1. Regularization; 2.1.1. Dimensionality control; 2.1.1.1. Truncated singular value decomposition2.1.1.2. Change of discretization; 2.1.1.3. Iterative methods; 2.1.2. Minimization of a composite criterion; 2.1.2.1. Euclidian distances; 2.1.2.2. Roughness measures; 2.1.2.3. Non-quadratic penalization; 2.1.2.4. Kullback pseudo-distance; 2.2. Criterion descent methods; 2.2.1. Criterion minimization for inversion; 2.2.2. The quadratic case; 2.2.2.1. Non-iterative techniques; 2.2.2.2. Iterative techniques; 2.2.3. The convex case; 2.2.4. General case; 2.3. Choice of regularization coefficient; ; 2.3.1. Residual error energy control; 2.3.2. "L-curve" method2.3.3. Cross-validation; 2.4. Bibliography; Chapter 3. Inversion within the Probabilistic Framework; 3.1. Inversion and inference; 3.2. Statistical inference; 3.2.1. Noise law and direct distribution for data; 3.2.2. Maximum likelihood estimation; 3.3. Bayesian approach to inversion; 3.4. Links with deterministic methods; 3.5. Choice of hyperparameters; 3.6. A priori model; 3.7. Choice of criteria; 3.8. The linear, Gaussian case; 3.8.1. Statistical properties of the solution; 3.8.2. Calculation of marginal likelihood; 3.8.3. Wiener filtering; 3.9. Bibliography; Part II. DeconvolutionChapter 4. Inverse Filtering and Other Linear Methods; 4.1. Introduction; 4.2. Continuous-time deconvolution; 4.2.1. Inverse filtering; 4.2.2. Wiener filtering; 4.3. Discretization of the problem; 4.3.1. Choice of a quadrature method; 4.3.2. Structure of observation matrix H; 4.3.3. Usual boundary conditions; 4.3.4. Problem conditioning; 4.3.4.1. Case of the circulant matrix; 4.3.4.2. Case of the Toeplitz matrix; 4.3.4.3. Opposition between resolution and conditioning; 4.3.5. Generalized inversion; 4.4. Batch deconvolution; 4.4.1. Preliminary choices; 4.4.2. Matrix form of the estimate4.4.3. Hunt's method (periodic boundary hypothesis); 4.4.4. Exact inversion methods in the stationary case; 4.4.5. Case of non-stationary signals; 4.4.6. Results and discussion on examples; 4.4.6.1. Compromise between bias and variance in 1D deconvolution; 4.4.6.2. Results for 2D processing; 4.5. Recursive deconvolution; 4.5.1. Kalman filtering; 4.5.2. Degenerate state model and recursive least squares; 4.5.3. Autoregressive state model; 4.5.3.1. Initialization; 4.5.3.2. Criterion minimized by Kalman smoother; 4.5.3.3. Example of result; 4.5.4. Fast Kalman filtering
• Sommario/riassunto: Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation. The concept of inverse problems precisely originates from the idea of inverting the laws of physics to recover a quantity of interest from measurable data.Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise