Full Text:   <1263>

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CLC number: TP13

On-line Access: 2022-08-22

Received: 2021-12-03

Revision Accepted: 2022-08-29

Crosschecked: 2022-02-23

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714


Yongyi Yan




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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.8 P.1239-1246


A matrix-based static approach to analysis of finite state machines

Author(s):  He DENG, Yongyi YAN, Zengqiang CHEN

Affiliation(s):  College of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China; more

Corresponding email(s):   yyyan@mail.nankai.edu.cn

Key Words:  Logical systems, Finite-valued systems, Semi-tensor product of matrices, Finite state machines, Matrix approaches

He DENG, Yongyi YAN, Zengqiang CHEN. A matrix-based static approach to analysis of finite state machines[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(8): 1239-1246.

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author="He DENG, Yongyi YAN, Zengqiang CHEN",
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T1 - A matrix-based static approach to analysis of finite state machines
A1 - He DENG
A1 - Yongyi YAN
A1 - Zengqiang CHEN
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
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SP - 1239
EP - 1246
%@ 2095-9184
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2100561

Traditional matrix-based approaches in the field of finite state machines construct state transition matrices, and then use the powers of the state transition matrices to represent corresponding dynamic transition processes, which are cornerstones of system analysis. In this study, we propose a static matrix-based approach that revisits a finite state machine from its structure rather than its dynamic transition process, thus avoiding the "explosion of complexity" problem inherent in the existing approaches. Based on the static approach, we reexamine the issues of closed-loop detection and controllability for deterministic finite state machines. In addition, we propose controllable equivalent form and minimal controllable equivalent form concepts and give corresponding algorithms.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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