In this paper we discuss a uniform family of circuits, realizing neural networks to solve approximately the maximum 2-satisfiability problem. An implementation on FPGA for the problem instances of 16 variables and 480 clauses is presented. The circuit shows a good performance solving problem instances in 20 μs with relative error less than 0.003

A Neural Circuit for the Maximum 2-Satisfiability Problem

POSENATO, Roberto
1995

Abstract

In this paper we discuss a uniform family of circuits, realizing neural networks to solve approximately the maximum 2-satisfiability problem. An implementation on FPGA for the problem instances of 16 variables and 480 clauses is presented. The circuit shows a good performance solving problem instances in 20 μs with relative error less than 0.003
0818670312
neural circuit; Approximation algorithms; Circuits; Expert systems; Field programmable gate arrays; Hopfield neural networks; Neural networks; Polynomials
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/16332
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