qiuqiangkong/matlab-hmm - Open source HMM toolbox, with Discrete-HMM, Gaussian-HMM.
Offers many examples to supplement mathematical notation when explaining new concepts PRML/PRMLT - Matlab code of machine learning algorithms in book PRML.Discusses the translation of HMM concepts from the realm of formal mathematics into computer code.The code is fully optimized yet is succinct so that user can easily learn the algorithms. In addition, the Kalman smoothing and minimal redundancy maximal relevance (mRMR) algorithm is used to improve the recognition accuracy. It Includes Viterbi, HMM filter, HMM smoother, EM algorithm for learning the parameters of HMM, etc. Covers the analysis of both continuous and discrete Markov chains This package contains functions that model time series data with HMM.Presents a broad range of concepts related to Hidden Markov Models (HMM), from simple problems to advanced theory.This approach, by means of analysis followed by synthesis, is suitable for those who want to study the subject using a more empirical approach. The unique feature of this book is that the theoretical concepts are first presented using an intuition-based approach followed by the description of the fundamental algorithms behind hidden Markov models using MATLAB. ABSTRACT The hidden Markov model (HMM) has been a workhorse of single-molecule data analysis and is now commonly used as a stand-alone tool in time series. Moreover, it presents the translation of hidden Markov models’ concepts from the domain of formal mathematics into computer codes using MATLAB. The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there. Unlike other books on the subject, it is generic and does not focus on a specific theme, e.g. The following matlab project contains the source code and matlab examples used for hidden markov model. Hidden Markov Models: Theory and Implementation using MATLAB presents, in an integrated form, both the analysis and synthesis of three different types of hidden Markov models.