Non-Separable Meyer-like Wavelet Frames
Mathematics, 2022 In the theory of wavelet frames, the known Daubechies wavelet bases have been generalized to compactly supported (Daubechies-like) wavelet frames, while the known bandlimited Meyer wavelet bases have not been generalized to date.
Zhihua Zhang
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Full Bayesian wavelet inference with a nonparametric prior [PDF]
, 2012 In this paper,we introduce a new Bayesian nonparametric model for estimating an unknown function in the presence of Gaussian noise.The proposed model involves a mixture of a point mass and an arbitrary (nonparametric) symmetric and unimodal distribution
Wang, Xue, Walker, Stephen G.
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Wavelets and Lattice Field Theory. [PDF]
EPJ Web of Conferences, 2018 When continuous fields are expanded in a wavelet basis, a D-dimensional continuum action becomes a (D+1)-dimensional lattice action on the naively discretized Poincare-patch coordinates of an Euclidean AdS(D+1). New possible criteria for acceptable actions open up.
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Intelligent CWFNN-AMF Controlled UPQC for Power-Quality Enhancement and DC-Link Voltage Regulation
EnergiesA unified power quality conditioner (UPQC) is developed for the mitigation of grid-voltage and -current distortions under steady-state and dynamic conditions.
Chin-Chan Cheng +2 more
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A digital twin framework with MobileNetV2 for damage detection in slab structures
Fracture and Structural IntegrityIn this study, a digital twin framework is proposed for damage detection in a civil structure, which consists of a finite element model, neural networks, model updating methods, and signal processing.
Duong Huong Nguyen +2 more
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Wavelet Estimation of an Unknown Function Observed with Correlated Noise [PDF]
, 2010 In many practical applications of nonparametric regression, it is desirable to allow for the possibility that the noise is correlated. In this paper, we focus on wavelet-based nonparametric function estimation and propose two distinct methods for ...
Wang, Xue +2 more
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Wavelet shrinkage using adaptive structured sparsity constraints [PDF]
, 2015 Structured sparsity approaches have recently received much attention in the statistics, machine learning, and signal processing communities. A common strategy is to exploit or assume prior information about structural dependencies inherent in the data ...
Tomassi, Diego Rodolfo +7 more
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Application of Combined Artificial Neural Network and Wavelet Theory for Flow Rate Prediction and Comparing the Results with those of ANFIS (Case Study: The Kor River) [PDF]
مهندسی منابع آب, 2015 Due to the prolonged droughts in the recent decades, the importance of predicting the flow rate of surface water in rivers for water resources management increases.
A. YazdanPanah, N. Barahmand
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Bosonic entanglement renormalization circuits from wavelet theory
SciPost Physics, 2021 Entanglement renormalization is a unitary real-space renormalization scheme. The corresponding quantum circuits or tensor networks are known as MERA, and they are particularly well-suited to describing quantum systems at criticality.
Freek Witteveen, Michael Walter
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Wavelets and filter banks: theory and design
IEEE Transactions on Signal Processing, 1992 The wavelet transform is compared with the more classical short-time Fourier transform approach to signal analysis. Then the relations between wavelets, filter banks, and multiresolution signal processing are explored. A brief review is given of perfect reconstruction filter banks, which can be used both for computing the discrete wavelet transform ...
Martin Vetterli, Cormac Herley
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