Search Results for "hidden markov java"

Java Modelling Tools is a suite of scientific tools for performance analysis and modelling using queueing theory and colored stochastic Petri nets. Models are solved either with analytical, asymptotic or simulation methods; workload characterization tools are also included in the suite. See the project website for more details: http://jmt.sf.net

JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.

UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy.

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.

The software annotates text with 41 broad semantic categories (Wordnet supersenses) for both nouns and verbs; i.e., it performs both sense disambiguation and named-entity recognition. The tagger implements a discriminatively-trained Hidden Markov Model.

ConoSorter is a high-throughput standalone program that implements regular expressions and profile Hidden Markov Models (pHMMs) for large-scale identification and classification of precursor conopeptides into gene superfamilies and classes based on the ER signal, pro-, and mature conopeptide regions generated from raw next-generation transcriptomic or proteomic data. ConoSorter also generates a set of relevant additional information (frequency of protein sequences, length, number of cysteine residues, hydrophobicity rate of N-terminal region) and automatically searches ConoServer database to allow the user to assess the reliability and relevance of the results and to aid the identification of new conopeptide superfamilies and classes.

HYDRA is an open-source, platform-neutral library for performing Markov Chain Monte Carlo. It implements the logic of standard MCMC samplers within a framework designed to be easy to use and to extend while allowing integration with other software to

This project provide hidden Markov model speech recognition system by using Matlab/Simulink/Stateflow.

The AK toolkit is another kit for building and use Hidden Markov Models (HMMs). Originally developed for handwritten text recognition (HTR) using Bernoulli HMMs, it also implements diagonal Gaussians and can be used for any other purpose.

EvoPromoter is a JAVA application that detects promoter regions in aligned nucleotide sequences using phylogenetic hidden markov models.

Trofast is an intelligent spell checker library based on statistical analysis developed for the Danish language. It makes use of n-grams, hidden Markov models and the Viterbi-algorithm.

ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.

Pamvotis is a Wireless LAN Simulator for all the current physical layer extentions of the IEEE 802.11 (IEEE 802.11 a/b/g) standard and for the IEEE 802.11e Draft for Quality of Service in WLANs.

RefineHMM refines an original hidden Markov model (HMM) to find an optimal fit against the evolutionary group that the HMM models, and it does this using through iterative database searches and incremental subsequent adaptation of the seed set.

D-finder is a bioinformatic search algorithm for the identification of D-sites in JNK interacting proteins. The algorithm is a combination of pattern matching and a hidden markov model (HMM) based on a training set of known JNK D-sites.

Software package for building, training and scoring hidden Markov models (HMMs).

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.

Algorithms to estimate the number of k-colorings of a low-degree graph using samplings from a markov chain are provided.

hmm2gviz is a tool used for converting hidden Markov models generated by HMMER into a graph visualization using Graphviz.

HmmSDK is a hidden Markov model (HMM) software development kit written in Java. It consists of core library of HMM functions (Forward-backward, Viterbi, and Baum-Welch algorithms) and toolkits for application development.

This project will show how to implement the Hidden Markov Model approximations of Voice Recognition into embedded and low power systems.

CMATLIB is set of libraries for writing numerical applicatons. It includes support for neural-networks, hidden Markov models, kd-trees, and data smoothing. It may be used from C and Scheme programs.

Find sweeps using Hidden Markov models using a Matlab package

Two Markov-Chain-Monte-Carlo-algorithms ("Glauber Dynamics" and "Flip Dynamics") used for randomly sampling k-colorings of a graph.