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Application of Wavelet Analysis in Signal Processing

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DOI: 0.23977/acss.2021.050104 | Downloads: 20 | Views: 322

Author(s)

Yuantang Duan 1, Shiyuan Zhu 1, Hongliang Zheng 1

Affiliation(s)

1 School of Electronic Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Corresponding Author

Yuantang Duan

ABSTRACT

Signal analysis is a significant part of current information processing. In the early days, when the Fourier transform was mainly used for processing, only frequency domain analysis could be performed, resulting in incomplete signal analysis. Based on this, the wavelet transform introduces a time-domain window, which makes signal analysis more effective. Wavelet analysis is the inheritance and development of Fourier transform. This paper introduces the actual background of wavelet theory and the basic principles of wavelet transform. On the basis of the comparative analysis of Fourier transform and wavelet transform, it focuses on the application of Matlab wavelet analysis in speech signal analysis, denoising and compression.

KEYWORDS

Fourier transform, Wavelet analysis, Speech signal processing, Denoise, Compression

CITE THIS PAPER

Yuantang Duan, Shiyuan Zhu, Hongliang Zheng. Application of Wavelet Analysis in Signal Processing. Advances in Computer, Signals and Systems (2021) 5: 28-36. DOI: http://dx.doi.org/10.23977/acss.2021.050104

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