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
Estimation of Parkinson’s disease severity using speech features and extreme gradient boosting
Hunkar Can Tunc,Hunkar Can Tunc,Cemal Okan Sakar,Hulya Apaydin,Gorkem Serbes,Aysegul Gunduz,Melih Tutuncu,Fikret Gürgen +7 more
TL;DR: This study aims to estimate the severity of PD from voice recordings of the patients using motor Unified Parkinson's Disease Rating Scale (UPDRS) as the evaluation metric and investigates the effectiveness of using age and years passed since diagnosis as covariates together with speech features.
Journal ArticleDOI
Tunable Q-wavelet based ECG data compression with validation using cardiac arrhythmia patterns
TL;DR: In this paper, the authors proposed a novel ECG data compression technique based on the tunable Q-wavelet transform which provides adjustable parameters to achieve good compression performance, and they examined the effect of the proposed compression technique on cardiac arrhythmia classification.
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Aero-engine bearing fault detection: A clustering low-rank approach
TL;DR: This study first reveals the singular value coupled pattern among strong similarity structure, weak similarity structure and noises, which consequently yields the overlapping coherent pathology in the SVD-based low-rank domain from the nonlocal similarity perspective of vibration waveforms.
Journal ArticleDOI
Optimized Tunable Q Wavelet Transform based Drowsiness Detection from Electroencephalogram Signals
Smith K. Khare,Varun Bajaj +1 more
TL;DR: An optimized tunable Q wavelet transform (O-TQWT) is proposed for the adaptive selection of decomposition parameters by using different optimization algorithms.
Journal ArticleDOI
A fault pulse extraction and feature enhancement method for bearing fault diagnosis
TL;DR: In this paper, the authors proposed a fault pulse extraction and feature enhancement method for bearing fault diagnosis, where the bearing vibration signal is segmented in the time domain and a multi-scale alternating direction multiplier method for dictionary learning is used to extract fault impact signal from the segment signal.
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.
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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.