Publications related to Discrete wavelet transform

Signal Analysis Based on Complex Wavelet Signs

We propose a signal analysis tool based on the sign (or the phase) of complex wavelet coefficients, which we call a signature. The signature is defined as the fine-scale limit of the signs of a signal's complex wavelet coefficients. We show that the signat ...

Elsevier2017

Localized orthogonal decomposition method for the wave equation with a continuum of scales

Assyr Abdulle, Patrick Henning

In this paper we propose and analyze a new multiscale method for the wave equation. The proposed method does not require any assumptions on space regularity or scale-separation and it is formulated in the framework of the Localized Orthogonal Decomposition ...

American Mathematical Society2017

Optimal Representations of Sparse Stochastic Processes with Applications in Image Processing

Pedram Pad

We establish in the world of stochastic processes a theoretical relation between sparsity and wavelets. The underlying principle is to treat stochastic processes as generalized functions, which facilitates the study of their properties in a transform domai ...

EPFL2017

A Gaussian Source Coding Perspective on Caching and Total Correlation

Guillaume Jean Op 't Veld

Communication technology has advanced up to a point where children are getting unfamiliar with themost iconic symbol in IT: the loading icon. We no longer wait for something to come on TV, nor for a download to complete. All the content we desire is availa ...

EPFL2017

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

Discrete-Time Domain Modeling of Voltage Source Inverters in Standalone Applications: Enhancement of Regulators Performance by Means of Smith Predictor

Francisco Daniel Freijedo Fernández, Federico De Bosio

The decoupling of the capacitor voltage and inductor current has been shown to improve significantly the dynamic performance of voltage source inverters in standalone applications. However, the computation and pulse width modulation delays still limit the ...

Ieee-Inst Electrical Electronics Engineers Inc2017

On the Besov regularity of periodic Levy noises

Michaël Unser, Julien René Pierre Fageot, John Paul Ward

In this paper, we study the Besov regularity of Levy white noises on the d-dimensional torus. Due to their rough sample paths, the white noises that we consider are defined as generalized stochastic fields. We, initially, obtain regularity results for gene ...

Academic Press Inc Elsevier Science2017

Learning the weight matrix for sparsity averaging in compressive imaging

Jean-Philippe Thiran, Dimitris Perdios, Adrien Georges Jean Besson

We propose to map the fast iterative shrinkage-thresholding algorithm to a deep neural network (DNN), with a sparsity prior in a concatenation of wavelet bases, in the context of compressive imaging. We exploit the DNN architecture to learn the optimal wei ...

2017

Dictionary Learning Based on Sparse Distribution Tomography

Michaël Unser, Pedram Pad

We propose a new statistical dictionary learning algorithm for sparse signals that is based on an α-stable innovation model. The parameters of the underlying model—that is, the atoms of the dictionary, the sparsity index α and the dispersion of the transfo ...

P. Pad2017

Isogeometric analysis and proper orthogonal decomposition for parabolic problems

Alfio Quarteroni, Shengfeng Zhu

We investigate the combination of Isogeometric Analysis (IGA) and proper orthogonal decomposition (POD) based on the Galerkin method for model order reduction of linear parabolic partial differential equations. For the proposed fully discrete scheme, the a ...

Springer Heidelberg2017

Discrete wavelet transform

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Signal Analysis Based on Complex Wavelet Signs

Localized orthogonal decomposition method for the wave equation with a continuum of scales

Optimal Representations of Sparse Stochastic Processes with Applications in Image Processing

A Gaussian Source Coding Perspective on Caching and Total Correlation

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Discrete-Time Domain Modeling of Voltage Source Inverters in Standalone Applications: Enhancement of Regulators Performance by Means of Smith Predictor

On the Besov regularity of periodic Levy noises

Learning the weight matrix for sparsity averaging in compressive imaging

Dictionary Learning Based on Sparse Distribution Tomography

Isogeometric analysis and proper orthogonal decomposition for parabolic problems

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Localized orthogonal decomposition method for the wave equation with a continuum of scales

Optimal Representations of Sparse Stochastic Processes with Applications in Image Processing

Isogeometric analysis and proper orthogonal decomposition for parabolic problems

A Gaussian Source Coding Perspective on Caching and Total Correlation

Dictionary Learning Based on Sparse Distribution Tomography

Discrete-Time Domain Modeling of Voltage Source Inverters in Standalone Applications: Enhancement of Regulators Performance by Means of Smith Predictor

Learning the weight matrix for sparsity averaging in compressive imaging

On the Besov regularity of periodic Levy noises

Signal Analysis Based on Complex Wavelet Signs