Publications associées à The n-term Approximation of Periodic Generalized Levy Processes

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Statistics of Wavelet Coefficients for Sparse Self-Similar Images

Michaël Unser, Julien René Pierre Fageot, Emrah Bostan

We study the statistics of wavelet coefficients of non-Gaussian images, focusing mainly on the behaviour at coarse scales. We assume that an image can be whitened by a fractional Laplacian operator, which is consistent with an

∥ω∥ ^{ -\gamma }

spectral ...

IEEE2014

The n-term Approximation of Periodic Generalized Levy Processes

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Max-stable processes and stationary systems of Levy particles

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part I: Continuous-Domain Theory

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part II: Discrete-Domain Theory

Invariant manifolds with boundary for jump-diffusions

Statistics of Wavelet Coefficients for Sparse Self-Similar Images

The Stationary Behaviour of Fluid Limits of Reversible Processes is Concentrated on Stationary Points

On The Optimality Of Operator-Like Wavelets For Sparse Ar(1) Processes

On the Optimality of Operator-Like Wavelets for Sparse AR(1) Processes

FORWARD BROWNIAN MOTION

The Analog Formulation of Sparsity Implies Infinite Divisibility and Rules Out Bernoulli-Gaussian Priors

On The Optimality Of Operator-Like Wavelets For Sparse Ar(1) Processes

FORWARD BROWNIAN MOTION

Statistics of Wavelet Coefficients for Sparse Self-Similar Images

On the Optimality of Operator-Like Wavelets for Sparse AR(1) Processes

Invariant manifolds with boundary for jump-diffusions

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part II: Discrete-Domain Theory

The Analog Formulation of Sparsity Implies Infinite Divisibility and Rules Out Bernoulli-Gaussian Priors

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part I: Continuous-Domain Theory

Max-stable processes and stationary systems of Levy particles

The Stationary Behaviour of Fluid Limits of Reversible Processes is Concentrated on Stationary Points