DocumentCode :
3059783
Title :
Using fuzzy probabilistic neural network for fault detection in MEMS
Author :
Asgary, Reza ; Mohammadi, Karim
Author_Institution :
Electr. Eng. Dept., Iran Univ. of Sci. & Technol., Tehran, Iran
fYear :
2005
fDate :
8-10 Sept. 2005
Firstpage :
136
Lastpage :
140
Abstract :
There are different methods for detecting digital faults in electronic and computer systems. But for analog faults, there are some problems. This kind of faults consists of many different and parametric faults, which can not be detected by digital fault detection methods. One of the proposed methods for analog fault detection is neural networks. Fault detection is actually a pattern recognition task. Faulty and fault free data are different patterns which must be recognized. In this paper we use a probabilistic neural network for fault detection in MEMS. A fuzzy system is used to improve performance of the network. Finally different network results are compared.
Keywords :
electrical engineering computing; fault diagnosis; fuzzy neural nets; micromechanical devices; probability; MEMS; analog fault detection; fault free; fuzzy probabilistic neural network; pattern recognition; Electrical engineering; Electrical fault detection; Fault detection; Fuzzy neural networks; Intelligent networks; Kernel; Micromechanical devices; Neural networks; Pattern recognition; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications, 2005. ISDA '05. Proceedings. 5th International Conference on
Print_ISBN :
0-7695-2286-6
Type :
conf
DOI :
10.1109/ISDA.2005.96
Filename :
1578774
Link To Document :
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