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Volumn 5, Issue 3, 2001, Pages 114-118

Neural-network models of learning and memory: Leading questions and an emerging framework

Author keywords

[No Author keywords available]

Indexed keywords

ARCHITECTURE; ARTIFICIAL NEURAL NETWORK; ATTENTION; BRAIN MAPPING; BRAIN REGION; COGNITION; CONSCIOUSNESS; FEEDBACK SYSTEM; HYPOTHESIS; LEARNING; MEMORY; MODEL; SHORT SURVEY; SYNAPTIC TRANSMISSION;

EID: 0035282806     PISSN: 13646613     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1364-6613(00)01591-6     Document Type: Review
Times cited : (24)

References (27)
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  • 12
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    • Grossberg, S.1
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    • Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors
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    • Redistribution of synaptic efficacy between neocortical pyramidal neurons
    • (1996) Nature , vol.382 , pp. 807-810
    • Markram, H.1    Tsodyks, M.2
  • 21
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    • ARTMAP: supervised real-time learning and classification of nonstationary data by a self-organizing neural network
    • (1991) Neural Netw. , vol.4 , pp. 565-588
    • Carpenter, G.A.1
  • 22
    • 0000786096 scopus 로고    scopus 로고
    • Distributed activation, search, and learning by ART and ARTMAP neural networks
    • Proc. Int. Conf. Neural Netw. (ICNN'96), IEEE Press
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    • Distributed learning, recognition, and prediction by ART and ARTMAP neural networks
    • (1997) Neural Netw. , vol.10 , pp. 1473-1494
    • Carpenter, G.A.1
  • 24
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    • Distributed ARTMAP: a neural network for fast distributed supervised learning
    • (1998) Neural Netw. , vol.11 , pp. 793-813
    • Carpenter, G.A.1
  • 26
    • 0033237828 scopus 로고    scopus 로고
    • How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex
    • (1999) Spat. Vis. , vol.12 , pp. 163-185
    • Grossberg, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.