Noise-shaping Quantization Methods for Frame-based and Compressive Sampling Systems

TL;DR

This paper reviews recent advances in noise-shaping quantization methods that improve analog-to-digital conversion by controlling quantization error in frame-based and compressive sampling systems.

Contribution

It provides a comprehensive overview of recent progress in applying noise-shaping techniques to redundant linear and compressive sampling systems.

Findings

Enhanced quantization error distribution outside the signal spectrum

Successful application to frame-based sampling systems

Advances in non-linear compressive sampling systems

Abstract

Noise shaping refers to an analog-to-digital conversion methodology in which quantization error is arranged to lie mostly outside the signal spectrum by means of oversampling and feedback. Recently it has been successfully applied to more general redundant linear sampling and reconstruction systems associated with frames as well as non-linear systems associated with compressive sampling. This chapter reviews some of the recent progress in this subject.