Application and Optimization of Continuous Wavelet Transform in Weak Impulse Signal Processing

Penghui Wu; Guoji Xu

doi:10.6919/ICJE.202412_10(12).0001

Authors

Penghui Wu
Guoji Xu

DOI:

https://doi.org/10.6919/ICJE.202412_10(12).0001

Keywords:

Continuous Wavelet Transform (CWT); Weak Signal Processing; Impulsive Signals; Feature Extraction; Denoising; Signal Enhancement; Parameter Optimization; Wavelet Basis Selection; Signal-To-Noise Ratio (SNR); Unsteady Signals.

Abstract

This paper investigates the application and optimization method of continuous wavelet transform (CWT) in weak impulse signal processing. Weak impulse signals widely exist in many fields, but the low signal strength and susceptibility to noise interference make signal detection and feature extraction challenging. The continuous wavelet transform shows superior signal processing potential by virtue of its multi-scale analysis capability and sensitivity to non-stationary signals. This paper firstly introduces the basic principle of wavelet transform, and analyzes the application of CWT in signal feature extraction, denoising and pulse detection; subsequently, for the high computational complexity and parameter selection problems of CWT in practical applications, optimization strategies such as wavelet basis and scale parameters are proposed, and the effectiveness of the optimization method is verified through experiments. It is shown that the optimized CWT method significantly improves the detection accuracy and processing efficiency of weak signals, and provides a reliable solution for accurately extracting and identifying weak pulse signals.

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