000			nam a22 7a 4500
999			_c29549 _d29549
008			190528b xxu||||| |||| 00| 0 eng d
020			_a9781138112056 _c(pbk)
082			_a629.8 _bWAN
100			_aWang, Cong
245			_aDeterministic learning theory : for identification, recognition, and control
260			_aBoca Raton : _bCRC Press, _c2010
300			_axviii, 195 p. : _bill. ; _c23.5 cm.
365			_aGBP _b61.99 _d00
490			_aAutomation and control engineering
504			_aIncludes bibliographical references and index.
520			_aDeterministic 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.
650			_aControl theory
650			_aIntelligent control systems
650			_aNeural networks
700			_aHill, David J. _eaut
942			_2ddc _cBK