Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Synthesis of GBSB-based Neural Associative Memories Using Evolution Program

  • Hyuk Cho (Department of Computer Science, Korea University, Chochiwon) ;
  • Park, Joo-young (Department of Control and Instrumentation Engineering, Korea University) ;
  • Moon, Jong-sub (Department of Electronic and information Engineering, Korea University, Chochiwon) ;
  • Park, Dai-hee (Department of Computer Science, Korea University, Chochiwon)
  • Published : 2001.12.01
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Abstract

In this paper, we propose a reliable method for searching the optimally performing generalized brain-state-in-a-box (GBSB) neural associative memory using an evolution program (EP) given a set of prototype patterns to be stored as stable equilibrium points. First, we exploit some qualitative guidelines necessary to synthesize the GBSB model. Next, we parameterize the solution space utilizing the limited number of parameters to represent the solution space. Then, we recast the synthesis of GBSB neural associative memories as two constrained optimization problems, which are equivalent to finding a solution to the original synthesis problem. Finally, we employ an evolution program (EP), which enables us to find an optimal set of parameters related to the size of domains of attraction (DOA) for prototype patterns. The validity of this approach is illustrated by a design example and computer simulations.

Keywords

References

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