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
Adaptive TQWT filter based feature extraction method and its application to detection of repetitive transients
Yun Kong,Tianyang Wang,Fulei Chu +2 more
TL;DR: It has been verified via numerical simulation that the proposed adaptive TQWT filter based feature extraction method can adaptively select TQ WT parameters and the optimum subband for repetitive transient detection without prior knowledge.
Journal ArticleDOI
Application of tunable-Q wavelet transform based nonlinear features in epileptic seizure detection
TL;DR: Experimental results illustrate efficacy of estimated features in epilepsy detection task and demonstrate that proposed methodology of nonlinear feature estimation preserves efficiency and simplicity and is appropriate for epileptic seizure detection.
Proceedings ArticleDOI
Focal EEG signal detection based on constant-bandwidth TQWT filter-banks
TL;DR: A new methodology based on constant-bandwidth tunable-Q wavelet transform (TQWT) filter banks has been designed for the identification of medically not curable focal epilepsy EEG signals.
Journal ArticleDOI
Fault feature enhancement for rotating machinery based on quality factor analysis and manifold learning
Meng Gan,Cong Wang,Chang’an Zhu +2 more
TL;DR: Results indicate that IES outperforms traditional empirical mode decomposition envelop analysis for diagnosing rotating machine faults and significantly improves the fault information with a highly regular representation, especially for weak fault-induced impulses.
Journal ArticleDOI
Simple Logistic Hybrid System Based on Greedy Stepwise Algorithm for Feature Analysis to Diagnose Parkinson’s Disease According to Gender
TL;DR: The Simple Logistic hybrid system based on the greedy stepwise search algorithm (SLGS) is presented as a novel approach that involves feature analysis to diagnose PD by gender and shows higher performance rates than the other study.
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.