Data compression in discriminating stochastic processes
Albert Perez · Czech digital mathematics library · 1974
In discriminating stochastic processes there arises a need of observation data reduction concerning the length of the realization to be considered as well as the variety (alphabet) of the instantaneous process states to be identified.In the paper a method for such data compression is given based on the theory of asymptotic discernibility of two stationary random processes as developed by the author for processes with memory.