An extrinsic EHW system for the evolutionary optimization and design of sequential circuit

The main obstacles in the evolutionary design of sequential circuits are the state assignment and the large evolution time for a complete circuit. In this paper, in order to minimize evolution time, a genetic algorithm (GA) based on a cost evolution of the circuit evolution is proposed to evolve a state assignment, which can lead to complexity reduction. A cost evaluation of the circuit evolution is uniquely defined as the fitness function of state assignment candidates. Under the GA-evolved state assignment, a novel LUT-based circuit evolution (LCE) is proposed to improve the search for a complete circuit. An extrinsic EHW system namely GALCE, which combines GA and LCE, aims to the evolutionary optimization and design of sequential circuit. This system is tested extensively on eight sequential circuits. The simulation results demonstrate the proposed approach can perform better in terms of average evolution time reduction and success rate.