Finite state machine state assignment targeting low power consumption

The authors present a genetic-algorithm-based approach for finite state machine synthesis that targets low power consumption. The approach follows a partitioning strategy to ensure that the states with a high transition probability between themselves are encoded to have smaller Hamming distances. The approach shows significant power savings in both two- and multi-level realisations of the resulting circuitry.