We present a novel method for state minimization of incompletely-specified finite state machines. Where classic methods simply minimize the number of states, ours directly addresses the implementation's logic complexity, and produces an exactly optimal implementation under input encoding. The method incorporates optimal ``state mapping'', i.e., the process of reducing the symbolic next-state relation which results from state splitting to an optimal conforming symbolic function. Further, it offers a number of convenient sites for applying heuristics to reduce time and space complexity, and is amenable to implementation based on implicit representations. Although our method currently makes use of an input encoding model, we believe it can be extended smoothly to encompass output encoding as well.
['Robert M. Fuhrer', 'Steven M. Nowick']
OPTIMIST: state minimization for optimal 2-level logic implementation