Deterministic learning theory : for identification, recognition, and control
By: Wang, Cong.
Contributor(s): Hill, David J [aut].
Material type:
BookSeries: Automation and control engineering.Publisher: Boca Raton : CRC Press, 2010Description: xviii, 195 p. : ill. ; 23.5 cm.ISBN: 9781138112056.Subject(s): Control theory | Intelligent control systems | Neural networksDDC classification: 629.8 Summary: Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural-control, effective representation and recognition of temporal patterns in a deterministic way.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Books | 629.8 WAN (Browse shelf) | Available | 031968 |
Includes bibliographical references and index.
Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural-control, effective representation and recognition of temporal patterns in a deterministic way.
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