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http://ktisis.cut.ac.cy/handle/10488/7234
Title: | A reservoir-driven non-stationary hidden markov model | Authors: | Demiris, Yiannis Chatzis, Sotirios P. Demiris, Yiannis |
Keywords: | Pattern recognition;Computer science;Markov processes | Category: | Electrical Engineering, Electronic Engineering, Information Engineering | Field: | Engineering and Technology | Issue Date: | 2012 | Publisher: | Elsevier | Source: | Pattern recognition, 2012, Volume 45, Issue 11, Pages 3985–3996 | Abstract: | In this work, we propose a novel approach towards sequential data modeling that leverages the strengths of hidden Markov models and echo-state networks (ESNs) in the context of non-parametric Bayesian inference approaches. We introduce a non-stationary hidden Markov model, the time-dependent state transition probabilities of which are driven by a high-dimensional signal that encodes the whole history of the modeled observations, namely the state vector of a postulated observations-driven ESN reservoir. We derive an efficient inference algorithm for our model under the variational Bayesian paradigm, and we examine the efficacy of our approach considering a number of sequential data modeling applications | URI: | http://ktisis.cut.ac.cy/handle/10488/7234 | ISSN: | 0031-3203 | DOI: | http://dx.doi.org/10.1016/j.patcog.2012.04.018 | Rights: | © 2012 Elsevier Ltd. All rights reserved | Type: | Article |
Appears in Collections: | Άρθρα/Articles |
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