Title: BSDT Multi-valued Coding in Discrete Spaces
Abstract: Recent binary signal detection theory (BSDT) employs a 'replacing' binary noise (RBN). In this paper it has been demonstrated that RBN generates some related N-dimensional discrete vector spaces, transforming to each other under different network synchrony conditions and serving 2-, 3-, and 4-valued neurons. These transformations explain optimal BSDT coding/decoding rules and provide a common mathematical framework, for some competing types of signal coding in neurosciences. Results demonstrate insufficiency of almost ubiquitous binary codes and, in complex cases, the need of multi-valued ones.
Publication Year: 2008
Publication Date: 2008-10-20
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 4
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