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Published in

2007 IEEE International Symposium on Information Theory

DOI: 10.1109/isit.2007.4557611

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Pattern Matching in Constrained Sequences

Proceedings article published in 2007 by Yongwook Choi ORCID, Wojciech Szpankowski
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Constrained sequences find applications in communication, magnetic recording, and biology. In this paper, we restrict our attention to the so-called (d,k) constrained binary sequences in which any run of zeros must be of length at least d and at most k, where 0 ¿ d ≪ k. In some applications one needs to know the number of occurrences of a given pattern w in such sequences, for which we coin the term constrained pattern matching. For a given word w or a set of words W, we estimate the (conditional) probability of the number of occurrences of w in a (d,k) sequence generated by a memoryless source. As a by-product, we enumerate asymptotically the number of (d,k) sequences with exactly r occurrences of a given word w, and compute Shannon entropy of (d,k) sequences with a given number of occurrences of w. Throughout this paper we use techniques of analytic information theory such as combinatorial calculus, generating functions, and complex asymptotics.