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A systematic EHW approach to the evolutionary design of sequential circuits

机译:系统的EHW方法用于时序电路的演进设计

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The main difficulty in the evolutionary design of finite state machines (FSMs) is lack of effective systematic EHW approach. To accomplish the evolutionary design of FSMs, a systematic EHW method named genetic programming-evolutionary strategy (GP-ES), which is a combination of ES and GP, is proposed. ES optimizes the state assignment and provide them to GP for population generation; GP is responsible for evolving the combinational part of FSM, and feeding the fitness of population back to ES for the evaluation of corresponding state assignments. GP-ES is tested extensively on twenty FSMs from MCNC Library. The results demonstrate that the GP-ES-derived state assignments are more efficient than the ones of Xia, Ali, Almaini and NOVA in the evolutionary design of FSMs. The results also illustrate that the GP-ES is superior to conventional synthesis tools in terms of complexity reduction for the design of small and middle FSMs. GP-ES also performs well in comparison with 3SD-ES in most cases.
机译:有限状态机(FSM)的进化设计中的主要困难是缺乏有效的系统EHW方法。为了完成FSM的进化设计,提出了一种系统的EHW方法,称为ES和GP的结合,称为遗传规划-进化策略(GP-ES)。 ES优化了状态分配,并将其提供给GP以生成种群; GP负责发展FSM的组合部分,并将人口适应度反馈给ES,以评估相应的州分配。 GP-ES已在来自MCNC Library的二十个FSM上进行了广泛的测试。结果表明,在FSM的进化设计中,GP-ES派生的状态分配比Xia,Ali,Almaini和NOVA的分配更有效。结果还表明,就中小型FSM的设计而言,GP-ES在降低复杂性方面优于常规综合工具。在大多数情况下,与3SD-ES相比,GP-ES的性能也不错。

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