State Minimization of General Finite Fuzzy Automata

The minimization of automaton is important to reduce space and computational time. Reduction in number of states and transitions leads to equivalent automaton with less number of states and transitions. In this paper, state minimization of General Finite Fuzzy Automata (GFFA) is discussed. To obtain minimal equivalent GFFA we have removed redundant states and transitions using substitution property (SP) partition and quotient machine. The algorithm to find membership values of states of the GFFA is described and algorithm to associate states with quotient machine to obtain minimal machine with less number of states is discussed.

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64028 Computational Time Reduction for Neurosurgical Training System Based on Finite Element Method(Biomechanics)

The Proceedings of the Asian Conference on Multibody Dynamics ◽

10.1299/jsmeacmd.2010.5._64028-1_ ◽

2010 ◽

Vol 2010.5 (0) ◽

pp. _64028-1_-_64028-7_

Author(s):

Osuke Kobayashi ◽

Kazuhiko Adachi ◽

Yohei Azuma ◽

Atsushi Fujita ◽

Eiji Kohmura

Keyword(s):

Finite Element Method ◽

Finite Element ◽

Training System ◽

Computational Time ◽

Neurosurgical Training ◽

Time Reduction ◽

Element Method

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812 Development of Neurosurgical Training System : 3rd report, Development of finite element model for computational time reduction

The Proceedings of Conference of Kansai Branch ◽

10.1299/jsmekansai.2010.85._8-12_ ◽

2010 ◽

Vol 2010.85 (0) ◽

pp. _8-12_

Author(s):

Osuke KOBAYASHI ◽

Kazuhiko ADACHI ◽

Youhei AZUMA ◽

Atsushi FUJITA ◽

Eiji KOHMURA

Keyword(s):

Finite Element ◽

Finite Element Model ◽

Element Model ◽

Training System ◽

Computational Time ◽

Neurosurgical Training ◽

Time Reduction

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On the State Minimization of Fuzzy Automata

IEEE Transactions on Fuzzy Systems ◽

10.1109/tfuzz.2014.2315620 ◽

2015 ◽

Vol 23 (2) ◽

pp. 434-443 ◽

Cited By ~ 18

Author(s):

Lvzhou Li ◽

Daowen Qiu

Keyword(s):

The State ◽

State Minimization ◽

Fuzzy Automata

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A Study on Computational Time Reduction of Road Obstacle Detection by Parallel Image Processor

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.2014.p0849 ◽

2014 ◽

Vol 18 (5) ◽

pp. 849-855 ◽

Cited By ~ 5

Author(s):

Yutaro Okamoto ◽

◽

Chinthaka Premachandra ◽

Kiyotaka Kato

Keyword(s):

Detection Algorithm ◽

Obstacle Detection ◽

Transport Systems ◽

Computational Time ◽

Intelligent Transport Systems ◽

Image Processor ◽

Intelligent Transport ◽

The Road ◽

Parallel Image ◽

Time Reduction

Automatic road obstacle detection is one of the significant problem in Intelligent Transport Systems (ITS). Many studies have been conducted for this interesting problem by using on-vehicle cameras. However, those methods still needs a dozens ofmillisecondsfor image processing. To develop the quick obstacle avoidance devices for vehicles, further computational time reduction is expected. Furthermore, regarding the applications, compact hardware is also expected for implementation. Thus, we study on computational time reduction of the road obstacle detection by using a small-type parallel image processor. Here, computational time is reduced by developing an obstacle detection algorithm which is appropriated to parallel processing concept of that hardware. According to the experimental evaluation of the new proposal, we could limit computational time for eleven milliseconds with a good obstacle detection performance.

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