Estimating Periodicities in Symbolic Sequences Using Sparse Modeling
Artikel i vetenskaplig tidskrift, 2015

In this paper, we propose a method for estimating statistical periodicities in symbolic sequences. Different from other common approaches used for the estimation of periodicities of sequences of arbitrary, finite, symbol sets, that often map the symbolic sequence to a numerical representation, we here exploit a likelihood-based formulation in a sparse modeling framework to represent the periodic behavior of the sequence. The resulting criterion includes a restriction on the cardinality of the solution; two approximate solutions are suggested-one greedy and one using an iterative convex relaxation strategy to ease the cardinality restriction. The performance of the proposed methods are illustrated using both simulated and real DNA data, showing a notable performance gain as compared to other common estimators.

symbolic sequences

Data analysis

spectral estimation




S. I. Adalbjornsson

Lunds universitet

J. Sward

Lunds universitet

Jonas Wallin

Chalmers, Matematiska vetenskaper, Matematisk statistik

Göteborgs universitet

A. Jakobsson

Lunds universitet

IEEE Transactions on Signal Processing

1053-587X (ISSN)

Vol. 63 8 2142-2150 7042782





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