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Published Articles >> Table of Contents >> Abstract
International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06)
p. 69
Granular Analysis of Time Sequence Based on Quotient Space
Liquan Zhao, University of Finance and Economics, China; Anhui University, China
Ling Zhang, Anhui University, China
Bo Zhang, Tsinghua University, China
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIMCA.2006.112
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| Abstract |
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This paper aims to carry out granular analysis of
time sequence based on quotient space. Granular
methods have long before been adopted to analyze
time sequence, but the granularity was based on time,
for example, day mean, month mean, year mean and so
on in finance forecast. In this paper, the granularity is
based on space and some significant results are
obtained: we can, in certain circumstances, get
characteristics of time sequence in an original space
when carrying out granular analysis of it in its
coarser-grain space; granular analysis of a Markov
chain is equivalent to an hidden Markov model
(HMM), contrarily, any HMM is equivalent to
granular analysis of a Markov chain. These results
deepened our understanding of HMM from the
perspective of granular analysis. We can not only use
the methods of HMM to study time sequence, but also
use the methods of granular analysis based on quotient
space theory to solve the problems of HMM.
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 Additional Information
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Index Terms- Quotient Space; Granular Computing; Markov Chain; HMM.
Citation:
Liquan Zhao, Ling Zhang, Bo Zhang,
"Granular Analysis of Time Sequence Based on Quotient Space,"
cimca,
p. 69,
International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06),
2006
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