DocumentCode :
2968976
Title :
A neural network model of short-term sequence memory
Author :
Futami, Ryoko ; Roshimiya, N.
Author_Institution :
Fac. of Eng., Tohoku Univ., Sendai, Japan
Volume :
3
fYear :
1993
fDate :
25-29 Oct. 1993
Firstpage :
2215
Abstract :
As a principle of temporal pattern processing in brain to encode arbitrary sequences, we indicate the effectiveness of "a pointer whose speed is adaptively changed by transitions in sequences", and the fact that this pointer can be realized by "propagation of local firing on one-dimensional nerve field whose symmetry is externally controlled". By computer simulation, we show that this principle enables the sequence encoding with nonlinear time length compression, retaining the memory trace as static firing patterns, and recalling the sequence with its original speed.
Keywords :
auditory evoked potentials; brain models; hearing; neurophysiology; recurrent neural nets; speech coding; brain model; computer simulation; local firing; memory trace; nerve field; neural network model; nonlinear time length compression; sequence encoding; short-term sequence memory; speech processing; static firing patterns; temporal pattern processing; Ambient intelligence; Biological neural networks; Character recognition; Computer simulation; Delay; Encoding; Nails; Neural networks; Pattern recognition; Recurrent neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
Type :
conf
DOI :
10.1109/IJCNN.1993.714166
Filename :
714166
Link To Document :
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