Genetic Algorithm Enlarges the Capacity of Associative Memory

نویسندگان

  • Akira Imada
  • Keijiro Araki
چکیده

We propose a genetic algorithm for mutually connected neural networks to obtain a higher capacity of associative memory. In Hop eld network as an associative memory system, the memory capacity is at most 15% of the number of neurons. Here we applied our method to the Hop eld network, and obtained the capacity of 33%. We conjectured that this is due to both asymmetry and sparseness of the connection matrix introduced by the genetic algorithm.

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تاریخ انتشار 1995