Journal ArticleDOI
Wavelet Transform With Tunable Q-Factor
TLDR
A discrete-time wavelet transform for which the Q-factor is easily specified and the transform can be tuned according to the oscillatory behavior of the signal to which it is applied, based on a real-valued scaling factor.Abstract:
This paper describes a discrete-time wavelet transform for which the Q-factor is easily specified. Hence, the transform can be tuned according to the oscillatory behavior of the signal to which it is applied. The transform is based on a real-valued scaling factor (dilation-factor) and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. Two forms of the transform are presented. The first form is defined for discrete-time signals defined on all of Z. The second form is defined for discrete-time signals of finite-length and can be implemented efficiently with FFTs. The transform is parameterized by its Q-factor and its oversampling rate (redundancy), with modest oversampling rates (e.g., three to four times overcomplete) being sufficient for the analysis/synthesis functions to be well localized.read more
Citations
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Journal ArticleDOI
Recent advancements of signal processing and artificial intelligence in the fault detection of rolling element bearings: a review
TL;DR: In this paper , the authors provide a summary of vibration analysis techniques for defect detection of rolling element bearing (REB) components, with a focus on vibration analysis with respect to REB defect detection.
Proceedings ArticleDOI
Resonance based analysis of acoustic waves for 3D deep-layer fingerprint reconstruction
TL;DR: The objective of this paper is to introduce a resonance based analysis of A-scan signals in the prototyped multi-transducer acoustic imaging system for 3D fingerprint imaging by offering fingerprint pattern reconstruction from deeper layers of skin via sweat duct locations and epidermis structure.
Journal ArticleDOI
Generalized Composite Multiscale Diversity Entropy and Its Application for Fault Diagnosis of Rolling Bearing in Automotive Production Line
Chuang Liang,Changzheng Chen +1 more
TL;DR: A new rolling bearing fault diagnosis framework which combined the GCMDiEn with the empirical wavelet transform (EWT), Laplacian score (LS), and particle swarm optimization-based support vector machine (PSO-SVM) was proposed.
Proceedings ArticleDOI
TQWT-based multi-scale dictionary learning for rotating machinery fault diagnosis
TL;DR: A novel algorithm named tunable Q-factor wavelet transform(TQWT)-based multi-scale dictionary learning for dealing with periodic impulses submerged in the heavy background noise for fault diagnosis of rotating machinery is proposed.
Book ChapterDOI
Electrocardiogram signal processing-based diagnostics: applications of wavelet transform
TL;DR: The basic background knowledge of the wavelet transforms and their recent applications in the processing of ECG signals for the diagnosis of various cardiovascular diseases are discussed.
References
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Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Journal ArticleDOI
Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Journal ArticleDOI
Atomic Decomposition by Basis Pursuit
TL;DR: Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having the smallest l1 norm of coefficients among all such decompositions.
Journal ArticleDOI
Fast Image Recovery Using Variable Splitting and Constrained Optimization
TL;DR: A new fast algorithm for solving one of the standard formulations of image restoration and reconstruction which consists of an unconstrained optimization problem where the objective includes an l2 data-fidelity term and a nonsmooth regularizer is proposed.
Journal ArticleDOI
Calculation of a constant Q spectral transform
TL;DR: In this article, a constant Q transform with a constant ratio of center frequency to resolution has been proposed to obtain a constant pattern in the frequency domain for sounds with harmonic frequency components.