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11th EAI International Conference on Mobile Multimedia Communications

Research Article

Research on Communication Signal Filtering Method Based on Generalized S-Transform

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  • @INPROCEEDINGS{10.4108/eai.21-6-2018.2276571,
        author={Ruowu Wu and Yongzhi Wang and Hui Han and Xiang Chen and Lin Yun},
        title={Research on Communication Signal Filtering Method Based on Generalized S-Transform},
        proceedings={11th EAI International Conference on Mobile Multimedia Communications},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2018},
        month={9},
        keywords={multimedia signal processing; generalized s transform; time-frequency filtering},
        doi={10.4108/eai.21-6-2018.2276571}
    }
    
  • Ruowu Wu
    Yongzhi Wang
    Hui Han
    Xiang Chen
    Lin Yun
    Year: 2018
    Research on Communication Signal Filtering Method Based on Generalized S-Transform
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.21-6-2018.2276571
Ruowu Wu1, Yongzhi Wang2, Hui Han1, Xiang Chen1, Lin Yun2,*
  • 1: State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), Luoyang, Henan, China
  • 2: College of Information and Communication Engineering, Harbin Engineering University, Harbin, China
*Contact email: linyun_phd@hrbeu.edu.cn

Abstract

In multimedia signal, because of the existence of Gaussian white noise in the environment, the speech signal is very vulnerable to pollution. In order to filter noise and extract useful components from signals, a speech signal filtering method based on generalized S transform and image processing is proposed in this paper. The method is compared with other two kinds of filtering methods. The simulation results show that, in the range of signal to noise ratio (SNR) -10dB~10dB, the filtering method can effectively improve the SNR more than 5dB, and its performance is the best

Keywords
multimedia signal processing; generalized s transform; time-frequency filtering
Published
2018-09-12
Publisher
EAI
http://dx.doi.org/10.4108/eai.21-6-2018.2276571
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