CNN templates learning based on tabu search

Abstract

This paper presents a novel CNN templates learning approach based on tabu search (TS), a meta-heuristic method for solving combinatorial optimal solutions. The TS method was applied to CNN with symmetric templates and was verified by simulations. Simulation experiments on intrusion detection have shown that the TS-based template learning algorithm exhibits superior performance in computation time to find the optimal solution and in the solution quality in contrast to the algorithm of GA and SA. © 2009 Binary Information Press. © 2009 Elsevier B.V., All rights reserved.