NDLI: Hidden Markov model parameters estimation with independent multiple observations and inequality constraints

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Micro & Nano Letters

The Journal of Engineering

Hidden Markov model parameters estimation with independent multiple observations and inequality constraints

Content Provider	IET Digital Library
Author	Xia, Lisha Fang, Huajing Liu, Xiaoyong
Abstract	In this study, the authors focus on hidden Markov model (HMM) parameters estimation with independent multiple observations and non-linear inequality constraints. The parameters estimation process is divided into four steps: initialisation, parameters pre-estimation, parameters re-estimation and termination. The pre-estimation results are used to approximate non-linear inequality constraints to linear inequality constraints. In parameters re-estimation step, the active-set optimisation is combined with the expectation maximisation (EM) algorithm in M-step and the active set-based EM algorithm is proposed to re-estimate HMM parameters when inequality constraints are not satisfied in pre-estimation. An auxiliary function is devised for reconstructing the optimisation objective function and the convergence of the proposed algorithm is also demonstrated. Simulation results indicate that the proposed algorithm provides better performance by modifying the random error of observation data appropriately and it is powerful for industry process fault diagnosis.
Starting Page	938
Ending Page	949
Page Count	12
ISSN	17519675
Volume Number	8
e-ISSN	17519683
Issue Number	Issue 9, Dec (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/8/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0505
Journal	IET Signal Processing
Publisher Date	2014-12-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Active Set-based EM Algorithm Active-set Optimisation Approximate Nonlinear Inequality Constraint Approximation Theory Expectation Maximisation Algorithm Expectation-maximisation Algorithm Fault Diagnosis Hidden Markov Model Hidden Markov Model Parameter Estimation HMM Parameter Estimation Independent Multiple Observation Industry Process Fault Diagnosis Initialisation Step Interpolation And Function Approximation Linear Inequality Constraint M-step Algorithm Markov Processes Nonlinear Estimation Numerical Analysis Numerical Approximation And Analysis Optimisation Optimisation Objective Function Reconstruction Optimisation Technique Parameter Estimation Parameter Pre-estimation Step Parameter Reestimation Step Probability Theory Random Error Modification Statistics Stochastic Linearised SCUC Termination Step
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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