Presentation | 1998/7/27 Unsupervised learning of temporal sequence coded by small interval differences Kenichi Amemori, Shin Ishii, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this report, we examine unsupervised learning of a sequence of sub-millisecond temporal coded information, in a network of neurons, which are assumed to have high temporal resolution. The input sequence is temporal information that needs the accuracy on the order of submilliseconds.The trained network works like an "associative memory"of the learned sequence, namely, the network responds when a newly input sequence is similar to the learned sequence.Consequently, the assembly of neurons is able to learn and distinguish an input sequence that carries information in the order of sub-milliseconds, although the spike emission intervals of the neurons are on the order of milliseconds. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Temporal coding / Unsupervised learning / Self-organization / Sequential learning / Associative memory |
Paper # | NC98-42 |
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Committee | NC |
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Conference Date | 1998/7/27(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Unsupervised learning of temporal sequence coded by small interval differences |
Sub Title (in English) | |
Keyword(1) | Temporal coding |
Keyword(2) | Unsupervised learning |
Keyword(3) | Self-organization |
Keyword(4) | Sequential learning |
Keyword(5) | Associative memory |
1st Author's Name | Kenichi Amemori |
1st Author's Affiliation | Nara Institute of Science and Technology() |
2nd Author's Name | Shin Ishii |
2nd Author's Affiliation | Nara Institute of Science and Technology |
Date | 1998/7/27 |
Paper # | NC98-42 |
Volume (vol) | vol.98 |
Number (no) | 219 |
Page | pp.pp.- |
#Pages | 8 |
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