An Information-Theoretic Approach to Analog-to-Digital Compression

Alon Kipnis, Yonina C. Eldar, Andrea J. Goldsmith

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Processing, storing, and communicating information that originates as an analog phenomenon involve conversion of the information to bits. This conversion can be described by the combined effect of sampling and quantization. The digital representation in this procedure is achieved by first sampling the analog signal so as to represent it by a set of discrete-time samples and then quantizing these samples to a finite number of bits. Traditionally, these two operations are considered separately. The sampler is designed to minimize information loss due to sampling based on prior assumptions about the continuous-time input. The quantizer is designed to represent the samples as accurately as possible, subject to the constraint on the number of bits that can be used in the representation. The goal of this chapter is to revisit this paradigm by considering the joint effect of these two operations and to illuminate the dependence between them.

Original languageEnglish (US)
Title of host publicationInformation-Theoretic Methods in Data Science
PublisherCambridge University Press
Pages44-71
Number of pages28
ISBN (Electronic)9781108616799
ISBN (Print)9781108427135
DOIs
StatePublished - Jan 1 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Engineering
  • General Computer Science
  • General Social Sciences
  • General Mathematics

Keywords

  • aliasing ADX
  • analog-to-digital conversion
  • digital-to-analog conversion
  • distortion rate
  • Nyquist sampling
  • rate distortion
  • sampling
  • Sub-Nyquist sampling

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