A Simplified Matrix Formulation for Sensitivity Analysis of Hidden Markov Models-Reference-Cited by-同舟云学术

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A Simplified Matrix Formulation for Sensitivity Analysis of Hidden Markov Models

Published:2017-08-22 Issue:3 Volume:10 Page:97
ISSN:1999-4893
Container-title:Algorithms
language:en
Short-container-title:Algorithms

Author:

Amsalu Seifemichael B.,Homaifar Abdollah,Esterline Albert

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Link

http://www.mdpi.com/1999-4893/10/3/97/pdf

Reference33 articles.

1. Speech recognition using hidden Markov model with MFCC-subband technique;Patel;Recent Trends Inf. Telecommun. Comput.,2010

2. Hidden Markov models in biological sequence analysis

3. Hidden Markov models in finance;Mamon,2014

4. Hidden Markov Models: Applications in Computer Vision;Bunke,2001

5. Driver behavior modeling near intersections using support vector machines based on statistical feature extraction;Amsalu;Intell. Veh. Symp.,2015

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A geometric characterization of sensitivity analysis in monomial models;International Journal of Approximate Reasoning;2022-12

2. Sensitivity analysis beyond linearity;International Journal of Approximate Reasoning;2019-10

3. Coal Seam Thickness Prediction Based on Transition Probability of Structural Elements;Applied Sciences;2019-03-18

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