23 citations · 23 across the 7 of their papers we have counts for
7 papers
Optimized Compressed Sensing Matrix Design for Noisy Communication Channels
Amirpasha Shirazinia, Subhrakanti Dey
We investigate a power-constrained sensing matrix design problem for a compressed sensing framework. We adopt a mean square error (MSE) performance criterion for sparse source reco…
Joint Source-Channel Vector Quantization for Compressed Sensing
Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund
We study joint source-channel coding (JSCC) of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a framework for realizing optimum JSCC schemes that enab…
Distributed Quantization for Compressed Sensing
Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund
We study distributed coding of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a distributed framework for realizing optimized quantizer that enables e…
Analysis-by-Synthesis Quantization for Compressed Sensing Measurements
Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund
We consider a resource-limited scenario where a sensor that uses compressed sensing (CS) collects a low number of measurements in order to observe a sparse signal, and the measurem…
Analysis-by-Synthesis-based Quantization of Compressed Sensing Measurements
Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund
We consider a resource-constrained scenario where a compressed sensing- (CS) based sensor has a low number of measurements which are quantized at a low rate followed by transmissio…
Channel-Optimized Vector Quantizer Design for Compressed Sensing Measurements
Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund
We consider vector-quantized (VQ) transmission of compressed sensing (CS) measurements over noisy channels. Adopting mean-square error (MSE) criterion to measure the distortion bet…