Numerical solutions for constrained quadratic problems using high-performance neural networks

Abstract

Two new classes of neural networks for solving constrained quadratic programming problems are presented. The main advantage of these networks is the requirement to use economic analog multipliers for variables. The numerical simulations demonstrate that in the new neural networks not only the cost of the hardware implementation is not relatively expensive… (More)
DOI: 10.1016/j.amc.2004.10.091

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