Journal ArticleDOI
Wavelet Transform With Tunable Q-Factor
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 new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension
TL;DR: It appears that a system is in place to assist clinicians to diagnose seizures accurately in less time as the proposed model achieves perfect 100% classification sensitivity and is found to be outperforming all existing models in terms of classification sensitivity (CSE).
Journal ArticleDOI
A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform
C. Okan Sakar,Gorkem Serbes,Aysegul Gunduz,Hunkar Can Tunc,Hatice Nizam,Betul Erdogdu Sakar,Melih Tutuncu,Tarkan Aydin,M. Erdem Isenkul,Hulya Apaydin +9 more
TL;DR: The results show that TQWT performs better or comparable to the state-of-the-art speech signal processing techniques used in PD classification, and Mel-frequency cepstral and the tunable-Q wavelet coefficients, which give the highest accuracies, contain complementary information inPD classification problem resulting in an improved system when combined using a filter feature selection technique.
Journal ArticleDOI
A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery
Ming Zhao,Ming Zhao,Xiaodong Jia +2 more
TL;DR: In this paper, a reweighted singular value decomposition (RSVD) strategy is proposed for signal denoising and weak feature enhancement in a two-stage gearbox as well as train bearings.
Journal ArticleDOI
Feature extraction of rolling bearing’s early weak fault based on EEMD and tunable Q-factor wavelet transform
TL;DR: In this paper, an ensemble empirical mode decomposition (EEMD) is applied on the low Q-factor transient impact component and satisfactory extraction result is obtained, and the original signal of rolling bearing early weak fault is decomposed by EEMD and several intrinsic mode functions (IMFs) are obtained.
Journal ArticleDOI
Tunable-Q Wavelet Transform Based Multiscale Entropy Measure for Automated Classification of Epileptic EEG Signals
TL;DR: The performance measure of the proposed multi-scale entropy measure has been found to be comparable with the existing state of the art epileptic EEG signals classification methods studied using the same database.
References
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Journal ArticleDOI
Iterated filter banks with rational rate changes connection with discrete wavelet transforms
TL;DR: It is shown that if one is ready to put up with the loss of the shift property, rational iterated filter banks can be used in the same manner as if they were dyadic filter banks, with the advantage that rational dilation factors can be chosen closer to 1.
Journal ArticleDOI
Perceptually motivated wavelet packet transform for bioacoustic signal enhancement
TL;DR: Results, measured by both SNR and segmental SNR of the enhanced wave forms, indicate that the proposed method outperforms other approaches for a wide range of noise conditions.
Journal ArticleDOI
Design of Optimal Wavelet Packet Trees Based on Auditory Perception Criterion
TL;DR: The criterion minimizes a perceptual cost function based on Zwicker's model of the critical band structure and allocates an optimal number of terminating nodes at different decomposition depths of the WP tree.
Journal ArticleDOI
An Implementation of Rational Wavelets and Filter Design for Phonetic Classification
Ghinwa F. Choueiter,James Glass +1 more
TL;DR: This paper increases the flexibility in wavelet selection by taking advantage of the relationship between wavelets and filter banks and by designing new wavelets using filter design methods that adopt two filter design techniques that are referred to as filter matching and attenuation minimization.
Proceedings ArticleDOI
L0-based sparse approximation: two alternative methods and some applications
Javier Portilla,Luis A. Mancera +1 more
TL;DR: In this paper, two methods for sparse approximation of images under l 2 error metric were proposed, i.e., for typical images and overcomplete oriented pyramids, for image restoration.