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In this paper, a design procedure is presented for synthesizing associative memories based on the brain-state-in-a-box neural network model. The theoretical analysis herein guarantees that the desired memory patterns are stored as asymptotically stable equilibrium points with very few spurious states. In order to avoid extensive computation, learning and forgetting are utilized by adding patterns...
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