A method of hidden Markov model optimization for use with geophysical data sets

Abstract

Abstract. Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements: it should be consistent, require minimal parameter tuning, and produce scienti¯cally meaningful results in reasonable time. We introduce a hidden Markov model (HMM)-based method for analysis of geophysical data sets that attempts to address these issues. Our method improves on standard HMM methods and is based on the systematic analysis of structural local maxima of the HMM objective function. Preliminary results of the method as applied to geodetic and seismic records are presented.