000			01931 a2200265 4500
001			1138561819
005			20250317100416.0
008			250312042019xx eng
020			_a9781138561816
037			_bTaylor & Francis _cGBP 33.99 _fBB
040			_a01
041			_aeng
072	7		_aTHR _2thema
072	7		_aTHR _2bic
072	7		_aTEC007000 _2bisac
072	7		_aTEC061000 _2bisac
072	7		_a006.32 _2bisac
100	1		_aBahram Nabet
245	1	0	_aSensory Neural Networks
250			_a1
260			_bCRC Press _c20190125
300			_a194 p
520			_bSensory information is detected and transformed by sensory neural networks before reaching higher levels of processing. These networks need to perform significant processing tasks while being compatible with the following levels. Lateral inhibition is a mechanism of local neuronal interaction that produces significant global properties. This book discusses those sensory neural networks influenced by nonlinear lateral inhibition. It features biological bases of lateral inhibition models, computational properties of these models that stress their short term adaptive behavior, their relation to recent activity in neural networks and connectionist systems, their use for image processing applications, and their application to motion detection. Descriptions from different technologies of analog hardware implementations of these classes of networks are described and results from implementations that corroborate theoretical analysis and show technologically desirable applications are presented. The book also uses nonlinear mathematical techniques to analyze temporal and spatial behavior of models presented within the text. Sensory Neural Networks: Lateral Inhibition is an interdisciplinary work that will prove useful to neural network theorists, biologists, circuit designers, and vision scientists.
700	1		_aRobert Pinter _4A01
999			_c2858 _d2858