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Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 42-103
Full Name: Dake Chen
Position: Assistant Professor
Age: ON
Sex: Male
Address: School of Electronics and Information Engineering£¬Xi¡¯an Jiaotong University£¬ Xi¡¯an710049,China
Country: CHINA
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E-mail address: cdk126@126.com
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Title of the Paper: Application of Wavelet Neural network in Signal Processing of MEMS Accelerometer
Authors as they appear in the Paper: Dake Chen, Jiuqiang Han
Email addresses of all the authors: cdk126@126.com, jqhan@mail.xjtu.edu.cn
Number of paper pages: 10
Abstract: A new method with wavelet neural network is described to optimize the MEMS accelerometer for temperature independent sensitivity. Linear accelerations are measured and compensated by a thermocouple the fast algorithm which is used to deal with the nonlinearity error. The simulation results show that the MEMS accelerometer with compensation is characterized by an excellent temperature stability of the sensitivity with less than 0.1% variation for a temperature range -40¡æ to 100¡æ, while the variation of the acceleration without compensation is 8%. The proposed algorithm can be useful for realization of the high accuracy miniature gyroscope systems based on MEMS technology.
Keywords: Micro-electro-mechanical system; Wavelet neural network; MEMS accelerometer; Function approximation; Momentum factor.
EXTENSION of the file: .doc
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