A neural network assembly memory model based on an optimal binary signal detection theory
A ternary/binary data coding algorithm and conditions under which Hopfield networks implement optimal convolutional and Hamming decoding algorithms has been described. Using the coding/decoding approach (an optimal Binary Signal Detection Theory, BSDT) introduced a Neural Network Assembly Memory M...
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| Datum: | 2004 |
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| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Інститут програмних систем НАН України
2004
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| Schlagworte: | |
| Online Zugang: | https://nasplib.isofts.kiev.ua/handle/123456789/2306 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | A neural network assembly memory model based on an optimal binary signal detection theory / P.M. Gopych // Проблеми програмування. — 2004. — N 2,3. — С. 473-479. — Бібліогр.: 24 назв. — англ. |
Institution
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Zusammenfassung: | A ternary/binary data coding algorithm and conditions under which Hopfield networks implement optimal convolutional and Hamming
decoding algorithms has been described. Using the coding/decoding approach (an optimal Binary Signal Detection Theory, BSDT) introduced
a Neural Network Assembly Memory Model (NNAMM) is built. The model provides optimal (the best) basic memory performance
and demands the use of a new memory unit architecture with two-layer Hopfield network, N-channel time gate, auxiliary reference memory,
and two nested feedback loops. NNAMM explicitly describes the dependence on time of a memory trace retrieval, gives a possibility of
metamemory simulation, generalized knowledge representation, and distinct description of conscious and unconscious mental processes. A
model of smallest inseparable part or an “atom” of consciousness is also defined. The NNAMM’s neurobiological backgrounds and its
applications to solving some interdisciplinary problems are shortly discussed. BSDT could implement the “best neural code” used in nervous
tissues of animals and humans. |
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