This thesis investigates different approaches to enable the use of compressed sensing (CS)-based acquisition devices in resource-constrained environments relying on cheap, energy-efficient sensors. We consider the acquisition of structured low-complexity signals from excessively quantized 1-bit observations, as well as partial compressive measurements collected by one or multiple sensors. In both scenarios, the central goal is to alleviate the complexity of sensing devices in order to enable signal acquisition by simple, inexpensive sensors. In the first part of the thesis, we address the reconstruction of signals with a sparse Fourier transform from 1-bit time domain measurements. We propose a modification of the binary iterative hard thre...
Quantized compressive sensing (QCS) deals with the problem of coding compressive measurements of low...
Quantized compressive sensing (QCS) deals with the problem of coding compressive measurements of low...
Abstract We study rate-distortion (RD) performance of various single-sensor compressed sensing (CS)...
This thesis investigates different approaches to enable the use of compressed sensing (CS)-based acq...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
Abstract—Compressive sensing is a new signal acquisition tech-nology with the potential to reduce th...
Compressed Sensing (CS) is a novel mathematical framework that has revolutionized modern signal and ...
This paper studies the problem of reconstructing sparse or compressible signals from compressed sens...
In this paper we study the problem of reconstructing sparse or compressible signals from compressed ...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital con-verters (ADC...
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs...
Quantized compressive sensing (QCS) deals with the problem of coding compressive measurements of low...
Quantized compressive sensing (QCS) deals with the problem of coding compressive measurements of low...
Abstract We study rate-distortion (RD) performance of various single-sensor compressed sensing (CS)...
This thesis investigates different approaches to enable the use of compressed sensing (CS)-based acq...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
The field of quantized compressed sensing investigates how to jointly design a measurement matrix, q...
Abstract—Compressive sensing is a new signal acquisition tech-nology with the potential to reduce th...
Compressed Sensing (CS) is a novel mathematical framework that has revolutionized modern signal and ...
This paper studies the problem of reconstructing sparse or compressible signals from compressed sens...
In this paper we study the problem of reconstructing sparse or compressible signals from compressed ...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital con-verters (ADC...
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs...
Quantized compressive sensing (QCS) deals with the problem of coding compressive measurements of low...
Quantized compressive sensing (QCS) deals with the problem of coding compressive measurements of low...
Abstract We study rate-distortion (RD) performance of various single-sensor compressed sensing (CS)...