Abstract
State assignment (SA) for finite state machines (FSMs) is one of the main optimization problems in the synthesis of sequential circuits. It determines the complexity of its combinational circuit and thus area, delay, testability and power dissipation of its implementation. Particle swarm optimization (PSO) is a non-deterministic heuristic that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions called particles, and moving them around in the search-space according to a simple mathematical formulae. In this paper, we propose an improved binary particle swarm optimization (BPSO) algorithm and demonstrate its effectiveness in solving the state assignment problem in sequential circuit synthesis targeting area optimization. It will be an evident that the proposed BPSO algorithm overcomes the drawbacks of the original BPSO algorithm. Experimental results demonstrate the effectiveness of the proposed BPSO algorithm in comparison to other BPSO variants reported in the literature and in comparison to Genetic Algorithm (GA), Simulated Evolution (SimE) and deterministic algorithms like Jedi and Nova.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
