A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities

Guo, Tiantian, Zhang, Tongpo, Lim, Enggee ORCID: 0000-0003-0199-7386, Lopez-Benitez, Miguel ORCID: 0000-0003-0526-6687, Ma, Fei ORCID: 0000-0001-6099-480X and Yu, Limin (2022) A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities. IEEE ACCESS, 10. pp. 58869-58903.

Text
IEEE_Access_2022_2.pdf - Author Accepted Manuscript
Download (3MB) | Preview

Official URL: http://dx.doi.org/10.1109/access.2022.3179517

Abstract

As a general and rigid mathematical tool, wavelet theory has found many applications and is constantly developing. This article reviews the development history of wavelet theory, from the construction method to the discussion of wavelet properties. Then it focuses on the design and expansion of wavelet transform. The main models and algorithms of wavelet transform are discussed. The construction of rational wavelet transform (RWT) is provided by examples emphasizing the advantages of RWT over traditional wavelet transform through a review of the literature. The combination of wavelet theory and neural networks is one of the key points of the review. The review covers the evolution of Wavelet Neural Network (WNN), the system architecture and algorithm implementation. The review of the literature indicates the advantages and a clear trend of fast development in WNN that can be combined with existing neural network algorithms. This article also introduces the categories of wavelet-based applications. The advantages of wavelet analysis are summarized in terms of application scenarios with a comparison of results. Through the review, new research challenges and gaps have been clarified, which will serve as a guide for potential wavelet-based applications and new system designs.

Item Type:	Article
Uncontrolled Keywords:	Wavelet transforms, Transforms, Multiresolution analysis, Discrete wavelet transforms, Wavelet packets, Signal resolution, Continuous wavelet transforms, Wavelets, multiresolution analysis, wavelet transform, rational wavelets, wavelet neural network
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	23 May 2022 15:57
Last Modified:	15 Mar 2024 06:08
DOI:	10.1109/ACCESS.2022.3179517
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3155363