A. Torokhti and P. Howlett (Eds.)9780444530448, 0444530444
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. – Best operator approximation, – Non-Lagrange interpolation, – Generic Karhunen-Loeve transform – Generalised low-rank matrix approximation – Optimal data compression – Optimal nonlinear filtering |
Table of contents : Content: Preface Pages vii-viii Chapter 1 Overview Pages 1-6 Chapter 2 Nonlinear operator approximation with preassigned accuracy Original Research Article Pages 9-63 Chapter 3 Interpolation of nonlinear operators Original Research Article Pages 65-95 Chapter 4 Realistic operators and their approximation Original Research Article Pages 97-135 Chapter 5 Methods of best approximation for nonlinear operators Original Research Article Pages 137-225 Chapter 6 Computational methods for optimal filtering of stochastic signals Original Research Article Pages 229-290 Chapter 7 Computational methods for optimal compression and reconstruction of random data Original Research Article Pages 291-378 Bibliography Original Research Article Pages 379-393 Index Pages 395-397 |
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