LAMP_HMM 隐马尔科夫模型

LAMP_HMM v. 0.9 (C++) Authors: Daniel DeMenthon and Marc Vuilleumier Date: Feb. 1999 - Revised Jan. 2003 This package contains C++ code for applying Hidden Markov Models (HMMs) to files of observation data. We used Tapas Kanungo's HMM C code as a starting point. Main upgrades from Tapas Kanungo's code: 1. Observations can be vectors. 2. Components of an observation vector can use different numbers of symbols. 3. Observation probabilities can be modeled by histograms or by Gaussians. 4. Training can be accomplished by multiple observation sequences, defined in a file. 5. State durations can be modeled explicitly by Gamma distributions. 6. In addition to the Baum-Welch method, the much faster segmental k-means method can be selected for training.