2007Unpublished venueRequires access

Extracting signal frequency information in time/frequency domain by means of continuous wavelet transform

Wei Wu

Open publisher page 11 citations

Abstract

In this paper, the techniques for extracting signal frequency information in time/frequency domain by means of continuous wavelet transform are presented and the novel “Maximum Wavelet Coefficient Frequency-Time Curve” method, together with “Sum Wavelet Coefficient Curve” method are proposed to overcome some shortfalls of existing continuous wavelet transform in signal frequency extracting. The experimental data and the Matlab generated data are calculated with continuous wavelet transform, and further analyzed with four wavelet coefficient evaluation methods, including proposed methods, showing different evaluation method characteristics that can be a reference for choosing suitable methods for different applications.

About this research paper

What this paper is about

In this paper, the techniques for extracting signal frequency information in time/frequency domain by means of continuous wavelet transform are presented and the novel “Maximum Wavelet Coefficient Frequency-Time Curve” method, together with “Sum Wavelet Coefficient Curve” method are proposed to overcome some shortfalls of existing continuous wavelet transform in signal frequency extracting. The experimental data and the Matlab generated data are calculated with continuous wavelet transform, and further analyzed with four wavelet coefficient evaluation methods, including proposed methods, showing different evaluation method characteristics that can be a reference for choosing suitable methods for different applications.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

In this paper, the techniques for extracting signal frequency information in time/frequency domain by means of continuous wavelet transform are presented and the novel “Maximum Wavelet Coefficient Frequency-Time Curve” method, together with “Sum Wavelet Coefficient Curve” method are proposed to overcome some shortfalls of existing continuous wavelet transform in signal frequency extracting. The experimental data and the Matlab generated data are calculated with continuous wavelet transform, and further analyzed with four wavelet coefficient evaluation methods, including proposed methods, showing different evaluation method characteristics that can be a reference for choosing suitable methods for different applications.

Key concepts: Second-generation wavelet transform, Wavelet, Wavelet transform, Stationary wavelet transform, Harmonic wavelet transform, Discrete wavelet transform, Wavelet packet decomposition, Computer science

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