Seismic Simultaneous Source Separation via Patchwise Sparse Representation

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We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection–diffusion–reaction equations based on the COmpRessed SolvING (CORSING) paradigm. Combining the Petrov–Galerkin technique with the compressed ...

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We study 1D continuous-domain inverse problems for multicomponent signals. The prior assumption on these signals is that each component is sparse in a different dictionary specified by a regularization operators. We introduce a hybrid regularization functi ...

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We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized signals by projecting the microphone array recordings into the array manifolds ...

In this paper, a compressive sensing (CS) perspective to exemplar-based speech processing is proposed. Relying on an analytical relationship between CS formulation and statistical speech recognition (Hidden Markov Models HMM), the automatic speech recognit ...

Seismic Simultaneous Source Separation via Patchwise Sparse Representation

Chattez avec Graph Search

Wavelet-Fourier CORSING techniques for multidimensional advection-diffusion-reaction equations

Dictionary Learning for Two-Dimensional Kendall Shapes

Graph Signal Processing for Machine Learning: A Review and New Perspectives

A machine learning approach for mapping the very shallow theoretical geothermal potential

Sparse Dictionaries for Continuous-Domain Inverse Problems

A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms

Fourier-Domain Optimization for Image Processing

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

Sparse Modeling of Neural Network Posterior Probabilities for Exemplar-based Speech Recognition