Presentation | 1995/7/27 Memory capacity and noise analysis of an associative memory using multiple inputs Toshiaki Tanaka, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Associative memory models are mainly classified as : auto-association, hetero-association, and temporal association. These models store one-to-one correspondence between memory patterns in their connection weights. So these models are able to recall a stored pattern from a noisy one. To extend this recalling capability of associative memory, a new model with a connection weight storing many-to-many correspondence is presented. This model recalls one pattern from an input pattern sequence which has a variety of pattern combinations. Bit error probabilities on a recalled pattern, memory capacity, and the noise effect are analysed in this report. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | associative memory / mamy-to-many / memory / capacity / sparse coding / neural network |
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Committee | NC |
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Conference Date | 1995/7/27(1days) |
Place (in Japanese) | (See Japanese page) |
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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) | Memory capacity and noise analysis of an associative memory using multiple inputs |
Sub Title (in English) | |
Keyword(1) | associative memory |
Keyword(2) | mamy-to-many |
Keyword(3) | memory |
Keyword(4) | capacity |
Keyword(5) | sparse coding |
Keyword(6) | neural network |
1st Author's Name | Toshiaki Tanaka |
1st Author's Affiliation | Advanced Research Lab. Toshiba Corporation() |
Date | 1995/7/27 |
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Volume (vol) | vol.95 |
Number (no) | 189 |
Page | pp.pp.- |
#Pages | 8 |
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