Title :
Estimating the Lengths of Memory Words
Author :
Morvai, Gusztav ; Weiss, Benjamin
Author_Institution :
MTA-BME Stochastics Res. Group, Budapest
Abstract :
For a stationary stochastic process {Xn} with values in some set A, a finite word w isin AK is called a memory word if the conditional probability of X 0 given the past is constant on the cylinder set defined by X - K -1=w . It is a called a minimal memory word if no proper suffix of w is also a memory word. For example in a K-step Markov processes all words of length K are memory words but not necessarily minimal. We consider the problem of determining the lengths of the longest minimal memory words and the shortest memory words of an unknown process {Xn} based on sequentially observing the outputs of a single sample {xi1,xi2,...xin}. We will give a universal estimator which converges almost surely to the length of the longest minimal memory word and show that no such universal estimator exists for the length of the shortest memory word. The alphabet A may be finite or countable.
Keywords :
Markov processes; information theory; stochastic processes; Markov processes; conditional probability; memory words; minimal memory word; stationary stochastic process; universal estimator; H infinity control; Markov processes; Pattern recognition; Probability; Scholarships; State estimation; Statistical learning; Statistics; Stochastic processes; Markov chains; order estimation; probability; stationary processes; statistics; stochastic processes;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2008.926316