Real-time synthesis of sparsely interconnected neural associative memories.
basic_science · Level V
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Abstract
The problem of implementing associative memories using sparsely interconnected generalized Brain-State-in-a-Box (gBSB) network is addressed in this paper. In particular, a "designer" neural network that synthesizes the associative memories is proposed. An upper bound on the time required for the designer network to reach a solution is determined. A neighborhood criterion with toroidal geometry for the cellular gBSB network is analyzed, in which the number of adjacent cells is independent of the generic cell location. A design method of neural associative memories with prespecified interconnecting weights is presented. The effectiveness of the proposed synthesis method is demonstrated with numerical examples.