Method and apparatus for determining a number of states for a hidden Markov model in a signal processing system

摘要

A signal processing system processes a signal using a hidden Markov model (HMM) having a number of states determined at least in part based on application of an iterative algorithm to the model. The iterative algorithm adjusts the number of states of the model, based at least in part on closeness measures computed between the states, until the model satisfies a specified performance criterion. The model having the adjusted number of states is then utilized to determine a characteristic of the signal, and an action of the signal processing system is controlled based on the determined characteristic.