Optimized Hidden Markov Model based on Constrained Particle Swarm Optimization

11/07/2018
by   L. Chang, et al.
0

As one of Bayesian analysis tools, Hidden Markov Model (HMM) has been used to in extensive applications. Most HMMs are solved by Baum-Welch algorithm (BWHMM) to predict the model parameters, which is difficult to find global optimal solutions. This paper proposes an optimized Hidden Markov Model with Particle Swarm Optimization (PSO) algorithm and so is called PSOHMM. In order to overcome the statistical constraints in HMM, the paper develops re-normalization and re-mapping mechanisms to ensure the constraints in HMM. The experiments have shown that PSOHMM can search better solution than BWHMM, and has faster convergence speed.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 3

page 4

05/10/2020

Application of the Hidden Markov Model for determining PQRST complexes in electrocardiograms

The application of the hidden Markov model with various parameters in th...
06/29/2017

Using Second-Order Hidden Markov Model to Improve Speaker Identification Recognition Performance under Neutral Condition

In this paper, second-order hidden Markov model (HMM2) has been used and...
06/24/2021

Fundamental limits for learning hidden Markov model parameters

We study the frontier between learnable and unlearnable hidden Markov mo...
02/14/2021

A New Algorithm for Hidden Markov Models Learning Problem

This research focuses on the algorithms and approaches for learning Hidd...
01/23/2013

Learning Hidden Markov Models with Geometrical Constraints

Hidden Markov models (HMMs) and partially observable Markov decision pro...
06/03/2021

Attack Prediction using Hidden Markov Model

It is important to predict any adversarial attacks and their types to en...
12/27/2015

Statistical and Computational Guarantees for the Baum-Welch Algorithm

The Hidden Markov Model (HMM) is one of the mainstays of statistical mod...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.