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OMP with Unknown Filters for Multipath Channel Estimation

Publications associées (32)

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Design Of Steerable Filters For The Detection Of Micro-Particles

Michaël Unser, Cédric René Jean Vonesch, Frédéric Stauber

This paper presents two contributions. We first introduce a continuous-domain version of Principal-Component Analysis (PCA) for designing steerable filters so that they best approximate a given set of image templates. We exploit the fact that steerability ...

IEEE2013

Discovering relevant spatial filterbanks for VHR image classification

Devis Tuia

In very high resolution (VHR) image classification it is common to use spatial filters to enhance the discrimination among landuses related to similar spectral properties but different spatial characteristics. However, the filters types that can be used ar ...

2012

Optimal use of conservation and accessibility filters in microRNA target prediction

Jiri Vanicek, Ray Marcel Marin Florez

It is generally accepted that filtering microRNA (miRNA) target predictions by conservation or by accessibility can reduce the false discovery rate. However, these two strategies are usually not exploited in a combined and flexible manner. Here, we introdu ...

Public Library of Science2012

We present the characterization of dyed doped/modified Epocore resist (Microresist Technology, Germany) with three commercially-available dyes (Proquimac Color, Spain). After being doped with lilac, red and yellow dyes in a 1:2500 ratio (dye:Epocore, w:w), ...

Elsevier2012

Estimating multiple filters from stereo mixtures: a double sparsity approach

Rémi Gribonval

We consider the problem of estimating multiple filters from convolutive mixtures of several unknown sources. We propose to exploit both the time-frequency (TF) sparsity of the sources and the sparsity of the mixing filters. Our framework consists of: a) a ...

2011

A Wideband Doubly-Sparse Approach For MITO Sparse Filter Estimation

Rémi Gribonval

We propose an approach for the estimation of sparse filters from a convolutive mixture of sources, exploiting the time-domain sparsity of the mixing filters and the sparsity of the sources in the time-frequency (TF) domain. The proposed approach is based o ...

IEEE2011

Filter Learning for Linear Structure Segmentation

Pascal Fua, Engin Türetken, Vincent Lepetit, Germán González Serrano, Roberto Rigamonti

We introduce an approach to learning convolution filters whose joint output can be fed to a classifier that labels them as belonging to linear structures or not. The filters are learned using sparse synthesis techniques but we show that enforcing constrain ...

2011

Compressive Sampling of Multiple Sparse Signals Having Common Support Using Finite Rate of Innovation Principles

Martin Vetterli, Ali Hormati

In sensor networks and communication systems, one is often confronted with sampling multiple sparse signals having a common support set. Multipath channels in a multiple-input multiple-output (MIMO) wireless communication setting is an interesting example ...

Institute of Electrical and Electronics Engineers2011

Double Sparsity: Towards Blind Estimation of Multiple Channels

Rémi Gribonval

We propose a framework for blind multiple filter estimation from convolutive mixtures, exploiting the time-domain sparsity of the mixing filters and the disjointness of the sources in the time-frequency domain. The proposed framework includes two steps: (a ...

Springer-Verlag's2010

UMTS-WiFi Switchable Bandpass Filter

Julien Perruisseau-Carrier

In this paper a reconfigurable bandpass filter able to switch between WiFi and UMTS transmit band standards is presented. The filter is designed in such a way that center frequency and bandwidth specifications are precisely met by defining a switchable fil ...

2009