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ON SOLVING CONSTRAINED OPTIMIZATION PROBLEMS WITH NEURAL NETWORKS : A PENALTY FUNCTION METHOD APPROACH

Authors
Publisher
Purdue University
Publication Date
Keywords
  • Nonlinear Programming
  • Stability
  • Optimization
  • Circuit
  • Implementation
Disciplines
  • Computer Science

Abstract

This paper is concerned with utilizing analog circuits to solve various linear and nonlinear programming problems. The dynamics of these circuits are analyzed. Then, the previously proposed circuit implementations for solving optimization problems are examined. A new nonlinear programming network and its circuit implementation is then introduced which utilizes the nonlinearities to eliminate the problems encountered in previous circuit implementations.

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