Separation of interleaved Markov chains

Abstract

We study the problem of separating interleaved sequences from discrete-time finite Markov chains. Previous work has considered the setting where the Markov chains participating in the interleaving have disjoint alphabets. In this work, we consider the more general setting where the component chains' alphabets can overlap. We formulate the problem as a hidden Markov model (HMM) and develop a deinterleaving algorithm by modifying classical HMM estimation techniques to take advantage of the special structure of our deinterleaving problem. Numerical results verify the effectiveness of the proposed method.