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
A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform
TL;DR: An adaptive demodulation technique for bearing fault detection via the tunable-Q wavelet transform using Kurtosis as an effective indicator of signal impulsiveness to guide the merging of the sub-signals leading to a signal component which contains information most relevant to the bearing fault.
Journal ArticleDOI
EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier
TL;DR: The results clearly show that the proposed TQWT and RFE based emotion recognition framework is an effective approach for emotion recognition using EEG signals.
Book ChapterDOI
An Automated Lung Sound Preprocessing and Classification System Based OnSpectral Analysis Methods
TL;DR: The proposed algorithm, which has achieved 49.86% accuracy on a very challenging and rich dataset, is a promising tool to be used as preprocessor in lung disease decision support systems.
Journal ArticleDOI
Motor imagery tasks-based EEG signals classification using tunable-Q wavelet transform
Sachin Taran,Varun Bajaj +1 more
TL;DR: T tunable-Q wavelet transform (TQWT)-based feature extraction method is proposed for the classification of different MI tasks EEG signals and provides 96.89% MI tasks classification accuracy, which is the highest as compared to other existing same data set methods.
Journal ArticleDOI
Time-frequency analysis for bearing fault diagnosis using multiple Q-factor Gabor wavelets
TL;DR: Case studies and comparisons with the continuous Morlet wavelet transform (CMWT) and the tunable Q-factor wavelettransform (TQWT) demonstrate the effectiveness and superiority of the CMQGWT for bearing diagnostic information extraction and fault identification.
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.