Journal ArticleDOI
Wavelet Transform With Tunable Q-Factor
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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
Sparsity-assisted bearing fault diagnosis using multiscale period group lasso
TL;DR: A new method namedMultiscale period group Lasso (MPG Lasso) is proposed, which is a multiscale SR model performed in different wavelet subbands and uses nonconvex regularization functions to enhance sparsity within and across groups.
Journal ArticleDOI
A reliable approach to distinguish between transient with and without HFOs using TQWT and MCA
TL;DR: A new approach is proposed, which is a combination of tunable Q-factor wavelet transform (TQWT), morphological component analysis (MCA) and complex Morlet wavelet (CMW), which is remarkably reliable and robust for the detection of HFOs.
Journal ArticleDOI
SSWT and VMD Linked Mode Identification and Time-of-Flight Extraction of Denoised SH Guided Waves
TL;DR: An improved shear horizontal guided wave mode identification method using a variational mode decomposition (VMD) algorithm and a time-of-flight (TOF) extraction method using the synchrosqueezed wavelet transform (SSWT) algorithm is proposed.
Journal ArticleDOI
Exploiting Feature Selection and Neural Network Techniques for Identification of Focal and Nonfocal EEG Signals in TQWT Domain.
Muhammad Tariq Sadiq,Hesam Akbari,Ateeq Ur Rehman,Zuhaib Nishtar,Bilal Masood,Mahdieh Ghazvini,Jingwei Too,Nastaran Hamedi,Mohammed K. A. Kaabar,Mohammed K. A. Kaabar +9 more
TL;DR: In this paper, the authors proposed a novel method based on differential operator and Tunable Q-factor wavelet transform (TQWT) to distinguish the focal and non-focal signals.
Journal ArticleDOI
A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network
S. Ananda Kumar,M. S. P. Subathra,Nallapaneni Manoj Kumar,Maria Malvoni,N. J. Sairamya,S. Thomas George,Easter S. Suviseshamuthu,Shauhrat S. Chopra +7 more
TL;DR: A new islanding detection technique that is based on tunable Q-factor wavelet transform (TQWT) and an artificial neural network (ANN) is proposed for PV-DPG and it is understood that the proposed approach would provide suitable insights to detect an islanding issue.
References
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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.
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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.
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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.
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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.