The parameter estimation of HMM2 based on wavelet transformation
DU Shi-ping · Journal of Liaoning Normal University · 2007
Given the condition of the mutual dependence of the observation noise and the Markov chain, a new method to solve the parameter problems of Gaussian Mixture models in second-order Hidden Markov Models(HMM2) is proposed when the input signals are transformed by wavelet. Hereby we do not need to reestimate the system parameters according to the transformed data, whereas we can make a direct calculation with the output transformed wavelet parameters. The new method simplifies the calculation process avoiding keeping all the data.