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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A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal
Mehmet Baygin,Prabal Datta Barua,Sengul Dogan,Turker Tuncer,Sefa Key,U. Rajendra Acharya,Kang Hao Cheong +6 more
TL;DR: In this article , a shape-based local feature extractor is presented which uses the geometric shape of the frustum pattern to generate textural features and statistical features have been extracted in this model.
Journal ArticleDOI
A Review on the Role of Tunable Q-Factor Wavelet Transform in Fault Diagnosis of Rolling Element Bearings
TL;DR: The role of TQWT as a fault diagnosis tool in recent research works on REB is summarized to help the readers to understand the modern trends of T QWT in the fault diagnosis procedure of a machine component like REB.
Journal ArticleDOI
TQWT Based Features for Classification of ALS and Healthy EMG Signals
Kiran Pu,Abhiram N,Taran S,Bajaj +3 more
TL;DR: This study focuses on the extraction of features based on tunable-Q factor wavelet transform (TQWT) for classifying ALS and healthy EMG signals and obtained better classification results as compared to other existing methods.
Journal ArticleDOI
Joint ensemble empirical mode decomposition and tunable Q factor wavelet transform based sleep stage classifications
Zuo Huang,Bingo Wing-Kuen Ling +1 more
TL;DR: In this article , a joint ensemble empirical mode decomposition (EEMD) and tunable Q factor wavelet transform (TQWT) based method is proposed for performing the sleep stage classifications.
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Wavelet analysis of frequency chaos game signal: a time-frequency signature of the C. elegans DNA.
TL;DR: This paper proposes a new mapping technique based on the chaos game theory that it is called the frequency chaos game signal (FCGS), and uses the wavelet analysis because it provides access to information that can be obscured by other time-frequency methods such as the Fourier analysis.
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.