000			03618cam a22006138i 4500
001			on1154117989
003			OCoLC
005			20220711203616.0
006			m d | |
007			cr |||||||||||
008			200501s2020 nju ob 001 0 eng
010			_a 2020015458
040			_aDLC _beng _erda _cDLC _dOCLCO _dOCLCF _dYDX _dDG1 _dRECBK
019			_a1191839004
020			_a9781119705918 _q(epub)
020			_a1119705916
020			_a9781119705871 _q(adobe pdf)
020			_a1119705878
020			_z9781119705864 _q(cloth)
020			_a9781119705925 _q(electronic bk.)
020			_a1119705924 _q(electronic bk.)
020			_z111970586X
035			_a(OCoLC)1154117989 _z(OCoLC)1191839004
042			_apcc
050	0	0	_aBF371
082	0	0	_a153.1/20113 _223
049			_aMAIN
100	1		_aGhosh, Lidia, _eauthor. _99259
245	1	0	_aCognitive modeling of human memory and learning : _ba non-invasive brain-computer interfacing approach / _cLidia Ghosh, Artificial Intelligence Lab., Dept. of Electronics and Tele-Communication Engineering, Amit Konar, Artificial Intelligence Lab., Dept. of Electronics and Tele-Communication Engineering, Pratyusha Rakshit, Artificial Intelligence Lab., Dept. of Electronics and Tele-Communication Engineering.
263			_a2007
264		1	_aHoboken, New Jersey : _bWiley, _c[2020]
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bn _2rdamedia
338			_aonline resource _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"This book models human memory from a cognitive standpoint by utilizing brain activations acquired from the cortex by electroencephalographic (EEG) and functional near-infrared-spectroscopic (f-NIRs) means. It begins with an overview of the early models of memory. The authors then propose a simplistic model of Working Memory (WM) built with fuzzy Hebbian learning. A second perspective of memory models is concerned with Short-Term Memory (STM)-modeling in the context of 2-dimensional object-shape reconstruction from visually examined memorized instances. A third model assesses the subjective motor learning skill in driving from erroneous motor actions. Other models introduce a novel strategy of designing a two-layered deep Long Short-Term Memory (LSTM) classifier network and also deal with cognitive load assessment in motor learning tasks associated with driving. The book ends with concluding remarks based on principles and experimental results acquired in previous chapters"-- _cProvided by publisher.
588			_aDescription based on print version record and CIP data provided by publisher; resource not viewed.
590			_aJohn Wiley and Sons _bWiley Frontlist Obook All English 2020
650		0	_aMemory. _99260
650		0	_aBrain-computer interfaces. _99261
650		0	_aCognitive neuroscience. _99262
650		7	_aPSYCHOLOGY / Cognitive Psychology & Cognition. _2bisacsh _99263
650		7	_aBrain-computer interfaces. _2fast _0(OCoLC)fst01742078 _99261
650		7	_aCognitive neuroscience. _2fast _0(OCoLC)fst00866540 _99262
650		7	_aMemory. _2fast _0(OCoLC)fst01015913 _99260
655		4	_aElectronic books. _93294
700	1		_aKonar, Amit, _eauthor. _99264
700	1		_aRakshit, Pratyusha, _eauthor. _99265
776	0	8	_iPrint version: _aGhosh, Lidia. _tCognitive modeling of human memory and learning _dHoboken, New Jersey : Wiley, [2020] _z9781119705864 _w(DLC) 2020015457
856	4	0	_uhttps://doi.org/10.1002/9781119705925 _zWiley Online Library
942			_cEBK
994			_a92 _bDG1
999			_c69337 _d69337