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Proceedings Of 1993 International Joint Conference On Neural Networks

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Extracted memory from temporal patterns using adaptive resonance and recurrent network

Content Provider	IEEE Xplore Digital Library
Author	Araki, O.
Copyright Year	1993
Description	Author affiliation: Dept. of Cognitive & Neural Syst., Boston Univ., MA, USA (Araki, O.)
Abstract	Humans can recognize objects through receiving continuously huge temporal information including redundancy and noise, and can memorize them. This paper proposes a neural network model which extracts pre-recognized patterns from temporally sequential patterns which include redundancy, and memorizes the patterns temporarily. This model consists of an adaptive resonance system and a recurrent time-delay network. The extraction is executed by the matching mechanism of the adaptive resonance system, and the temporal information is processed and stored by the recurrent network. Simple simulations are examined to exemplify the property of extraction.
Starting Page	2642
Ending Page	2645
File Size	318863
Page Count	4
File Format	PDF
ISBN	0780314212
DOI	10.1109/IJCNN.1993.714266
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-10-25
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Resonance Data mining Adaptive systems Pattern recognition Biological neural networks Subspace constraints Pattern matching Equations Brain modeling Parallel processing
Content Type	Text
Resource Type	Article

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