International audienceIn this paper we consider the l 1-compressive sensing problem. We propose an algorithm specifically designed to take advantage of shared memory, vectorized, parallel and many-core microprocessors such as the Cell processor, new generation Graphics Processing Units (GPUs) and standard vectorized multi-core processors (e.g. quad-core CPUs). Besides its implementation is easy. We also give evidence of the efficiency of our approach and compare the algorithm on the three platforms, thus exhibiting pros and cons for each of them
This paper reports a field-programmable gate array (FPGA) design of compressed sensing (CS) using th...
This paper presents the design of a system, which can improve the reconstruction of Compressive Sens...
Today, a number of applications need to process large bandwidth signals. These applications frequent...
International audienceIn this paper we consider the l 1-compressive sensing problem. We propose an a...
This paper describes a parallel algorithm for solving the l(1)-compressive sensing problem. Its desi...
Abstract An application specific programmable processor is designed based on the analysis of a set ...
Compressive Sensing (CS) is a technique which allows a signal to be compressed at the same time as i...
Compressive sensing (CS) is a new signal processing method, which was developed recent years. CS can...
In this paper, a parallel implementation of a previously constrained hyperspectral coded aperture (C...
In this thesis, we are interested in adapting algorithms to parallel architectures. Current high per...
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform do...
This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA...
International audienceMixture of Gaussians (MoG) and compressive sensing (CS) are two common approac...
For appropriate matrix ensembles, greedy algorithms have proven to be an efficient means of solving ...
New possibilit ies exist for the development of novel hardware/software platforms havin g fast data ...
This paper reports a field-programmable gate array (FPGA) design of compressed sensing (CS) using th...
This paper presents the design of a system, which can improve the reconstruction of Compressive Sens...
Today, a number of applications need to process large bandwidth signals. These applications frequent...
International audienceIn this paper we consider the l 1-compressive sensing problem. We propose an a...
This paper describes a parallel algorithm for solving the l(1)-compressive sensing problem. Its desi...
Abstract An application specific programmable processor is designed based on the analysis of a set ...
Compressive Sensing (CS) is a technique which allows a signal to be compressed at the same time as i...
Compressive sensing (CS) is a new signal processing method, which was developed recent years. CS can...
In this paper, a parallel implementation of a previously constrained hyperspectral coded aperture (C...
In this thesis, we are interested in adapting algorithms to parallel architectures. Current high per...
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform do...
This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA...
International audienceMixture of Gaussians (MoG) and compressive sensing (CS) are two common approac...
For appropriate matrix ensembles, greedy algorithms have proven to be an efficient means of solving ...
New possibilit ies exist for the development of novel hardware/software platforms havin g fast data ...
This paper reports a field-programmable gate array (FPGA) design of compressed sensing (CS) using th...
This paper presents the design of a system, which can improve the reconstruction of Compressive Sens...
Today, a number of applications need to process large bandwidth signals. These applications frequent...