Deterministic Learning Theory for Identification, Recognition, and Control

CRC Press

Deterministic Learning Theory for Identification, Recognition, and ControlAuthor(s): Cong Wang, David J. Hill, Frank L. Lewis\nFormat: Paperback\nPublisher: Taylor & Francis Ltd, United Kingdom\nImprint: CRC Press\nISBN-13: 9781138112056, 978-1138112056\nSynopsis\nDeterministic 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. \n\nA Deterministic View of Learning in Dynamic Environments\n\nThe authors begin with an introduction to the concepts of deterministic learning theory, followed by a di.