Statistical Decision Theory In Adaptive Control Systems By Yoshikazu Sawaragi Yoshfumi Sunahara And Takayoshi Nakamizo

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Statistical Decision Theory in Adaptive Control Systems by Yoshikazu Sawaragi, Yoshfumi Sunahara and Takayoshi Nakamizo

Statistical Decision Theory in Adaptive Control Systems by Yoshikazu Sawaragi, Yoshfumi Sunahara and Takayoshi Nakamizo
Author :
Publisher : Elsevier
Total Pages : 231
Release :
ISBN-10 : 9780080955469
ISBN-13 : 0080955460
Rating : 4/5 (460 Downloads)

Book Synopsis Statistical Decision Theory in Adaptive Control Systems by Yoshikazu Sawaragi, Yoshfumi Sunahara and Takayoshi Nakamizo by : Yoshikazu Sawaragi

Download or read book Statistical Decision Theory in Adaptive Control Systems by Yoshikazu Sawaragi, Yoshfumi Sunahara and Takayoshi Nakamizo written by Yoshikazu Sawaragi and published by Elsevier. This book was released on 1967-01-01 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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; andmethods 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 particularbranches, 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


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