On the Design of BSB Neural Associative Memories Using Semidefinite Programming

Authors:
Jooyoung Park;Hyuk Cho;Daihee Park
Affiliations:
Department of Control and Instrumentation Engineering, Korea University, Chochiwon, Chungnam, 339-800, Korea;Department of Computer Science, Korea University, Chochiwon, Chungnam, 339-800, Korea;Department of Computer Science, Korea University, Chochiwon, Chungnam, 339-800, Korea
Venue:
Neural Computation
Year:
1999

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Abstract

This article is concerned with the reliable search for optimally performing BSB (brain state in a box) neural associative memories given a set of prototype patterns to be stored as stable equilibrium points. By converting and/or modifying the nonlinear constraints of a known formulation for the synthesis of BSB-based associative memories into linear matrix inequalities, we recast the synthesis into semidefinite programming problems and solve them by recently developed interior point methods. The validity of this approach is illustrated by a design example.