Affiliation:
1. University of Oklahoma
2. Zhejiang Sci-Tech University
Abstract
The stochastic resonance (SR) theory provides a new idea for the detection of weak signal submerged in the strong noise. Combined with the optimization theory, this paper puts forward a stochastic resonance system based on genetic algorithm and applied it in a low concentrations gas detection. Firstly we preprocessed the input signal to satisfy the requirements of SR system, then developed the genetic algorithm to seek the maximum output signal-to-noise ratio (SNR), which was used to evaluate the performance of the system. In the end the relationship between the maximum SNR and concentration of gas was analyzed. The results of the experiments indicated the proposed method could improve the detection ability and enhance the detection limit of low gas concentrations.
Publisher
Trans Tech Publications, Ltd.
Reference11 articles.
1. Benzi R., Sutera A., Vulpiana A: Phys. A, 14(11), 453-457(1981).
2. Yonggang Leng, Taiyong Wang, Yan Guo, et al: Phys. Soc. 56(1): 30-35. (2007).
3. Bin Xu, Fabing Duan, Ronghao Bao, et al: Chaos, Solitons& Fractals, 13(4): 633-644. (2002).
4. Yonggang Leng: Phys. Soc. (008): 5196-5200. (2009).
5. Guangzhan Cao, Hongjun Liu, Xuefeng Li, et al: Optics express, 22(4): 4214-4223. (2014).
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