Abstract—A novel algorithm called Cooperative Binary Iter- ative Hard Thresholding (CB-IHT) based on distributed 1-bit compressive sensing is proposed in�...

In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is�...

[0001]. This invention relates generally to reconstructing sparse signals, and more particularly to reconstructing sparse signals from distorted measurements.

Sep 20, 2012 � Abstract—The problem of distributed estimation of a paramet- ric physical field is stated as a maximum likelihood estimation problem.

A signal x is reconstructed by measuring the signal x as a vector y of measurements yi, wherein the measurements yi are distorted, and each measurement yi�...

Abstract—This paper presents Matched Sign Pursuit (MSP), a new greedy algorithm to perform sparse signal reconstruction from signs of signal measurements,�...

We address the problem of reconstructing a sparse signal from compressive measurements with the aid of multiple known correlated signals.

Abstract: Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS�...

In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown.

Jul 27, 2015 � Abstract—In this paper, we design and analyze distributed vector quantization (VQ) for compressed measurements of cor- related sparse�...