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 novel short-frequency slip fault energy distribution-based demodulation technique for gear diagnosis and prognosis:
TL;DR: A novel short-frequency slip fault energy distribution-based demodulation method that compares the fault-induced resonance energy ratio values of faulty gears with different severity is proved to be a reliable health indicator for gear prognostic.
Proceedings ArticleDOI
Comparative analysis of wavelet transform algorithms for image compression
TL;DR: The basic objective of this paper is to analyze the concept of wavelet based algorithms for image compression using different parameter and the algorithms involved in the comparative analysis are Wavelet Difference Reduction (WDR), Spatial orientation tree wavelet, Embedded zero tree wavelets, and modified Set Partitioning in hierarchical trees (SPIHT).
Journal ArticleDOI
Continuous Health Monitoring of Bearing by Oscillatory Sparsity Indices Under Non Stationary Time Varying Speed Condition
TL;DR: In this article , a sparsity index guided bearing health monitoring has been achieved after oscillation based decomposition of vibration signals, where low oscillatory component of a vibration signal is separated from the original signal with the help of tunable Q factor wavelet transform (TQWT) based on its ability to perform continuously under varying speed condition.
Journal ArticleDOI
An Intelligent Motor Imagery Detection System Using Electroencephalography with Adaptive Wavelets
TL;DR: Robust TQWT is proposed for automatically selecting optimum tuning parameters to decompose non-stationary EEG signals accurately and is superior to other state-of-the-art using the same database.
Journal ArticleDOI
Feature Enhancement Based on Regular Sparse Model for Planetary Gearbox Fault Diagnosis
TL;DR: In this article, based on the feature enhancement problem under strong interferences, a sparse regular diagnosis algorithm is studied and a new fault sensitivity indicator is constructed to distinguish different periodic impulse signals and enhance the energy of the fault impulse.
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.