System identification : advances and case studies
著者
書誌事項
System identification : advances and case studies
（Mathematics in science and engineering : a series of monographs and textbooks, v. 126）
Academic Press, 1976
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注記
Includes bibliographical references
"Academic Press rapid manuscript reproduction"—half title page verso
内容説明・目次
内容説明
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.
This book covers: best operator approximation, non-Lagrange interpolation, generic Karhunen-Loeve transform, generalised low-rank matrix approximation, optimal data compression, and optimal nonlinear filtering.
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