Abstract

An improved pulse coupled neural network(PCNN) model is proposed to solve combination optimization problem with help of PCNN auto-wave characteristic.Based on Tri-state cascading pulse coupled neural network(TCPCNN),a preventive feedback method by using the triangle inequality theorem is introduced.In the process of searching solutions,all solutions are judged by the triangle inequality theorem and solutions of poor quality are removed.Therefore,the solution space complexity of combinatorial optimization problems decreases and the efficiency and accuracy are improved.This algorithm is applied to the shor test path(SP) and the traveling salesman problem(TSP) simulations.The results show that the proposed algorithm can effectively reduce space complexity and further improve the searching speed.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.