A reservoir-driven non-stationary hidden Markov model

DOI10.1016/j.patcog.2012.04.018zbMath1242.68211OpenAlexW2101266302WikidataQ56115044 ScholiaQ56115044MaRDI QIDQ437781

Sotirios P. Chatzis, Yiannis Demiris

Publication date: 19 July 2012

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2012.04.018

zbMATH Keywords

reservoirhidden Markov modelDirichlet process

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Nonparametric inference (62G99)

Related Items (1)

Estimation of steady-state quantities of an HMM with some rarely generated emissions

Uses Software

• PRMLT

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Reservoir computing approaches to recurrent neural network training
• A variational Bayesian methodology for hidden Markov models utilizing Student's-\(t\) mixtures
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Estimating the dimension of a model
• Ferguson distributions via Polya urn schemes
• Nonparametric Bayesian data analysis
• An experimental unification of reservoir computing methods
• Inference in hidden Markov models.
• A Bayesian analysis of some nonparametric problems
• Bayesian Nonparametric Inference for Random Distributions and Related Functions
• 10.1162/15324430152748236
• Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
• Music Analysis Using Hidden Markov Mixture Models
• Hidden Markov Models With Stick-Breaking Priors
• Variational inference for Dirichlet process mixtures

This page was built for publication: A reservoir-driven non-stationary hidden Markov model