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
Author(s): Joseph La Salle and Solomon Lefschetz (Eds.)
Series: Mathematics in Science and Engineering 4
Publisher: Elsevier Science
Year: 1961
Language: English
Pages: iii-viii, 3-134
Content:
Edited by
Page iii
Copyright Page
Page iv
Preface
Pages v-vi
Errata
Page viii
1. Geometrie Concepts: Vectors and Matrices
Pages 3-20
2. Differential Equations
Pages 21-73
3. Application of Liapunov's Theory to Controls
Pages 75-105
4. Extensions of Liapunov's Method
Pages 107-130
Literature
Pages 131-132
Index
Pages 133-134