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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Book ChapterDOI
Separation of Impulse from Oscillation for Detection of Bearing Defect in the Vibration Signal
TL;DR: The proposed diagnostic procedure making use of Dual Q-Factor wavelet decomposition (DQWD) and adaptive wavelet transform (AWT) is effective over EMD and EEMD technique in isolating the transient impulse of defect from the oscillatory part of the signal.
Journal ArticleDOI
Stability selection for LASSO with weights based on AUC
TL;DR: In this paper , the authors proposed a weighted stability selection method to select variables by weighing them using the area under the receiver operating characteristic curve (AUC) from additional modelling, and evaluated the performance of the proposed method in terms of the true positive rate, positive predictive value (PPV), and stability of variable selection.
Proceedings ArticleDOI
Tool Wear State Identification Based on Frequency Domain Denoising and Frequencies-Separation Attention Networks
TL;DR: In this paper , a machine tool inherent characteristic frequency interception method and a time-frequency domain decoupling technique based on wavelet transform with tunable Q-factor are introduced to perform targeted noise removal during machining.
Journal ArticleDOI
EEG Classification Using TQWT and Classifiers
Sibasankar Padhy,S Sai Suryateja +1 more
TL;DR: The purpose of this study is to detect the epileptic seizures, which can be indicated by the abnormal disturbances in intracranial neurons using the electroencephalogram (EEG) signals, and Logistic Regression classifier has showed higher accuracy, specificity and sensitivity for NF-S and O-F-S groups in comparison to RF and DT classifiers.
Proceedings ArticleDOI
A multi-faults separation method based on improved sparse component analysis
TL;DR: A novel approach based on the sparsity of objective signals was proposed to effectively separate the multi-faults and achieve the fault diagnosis, but the vibration signals are scantily sparse and it usually cannot be represented in a sparse way.
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.