Comparison-limited Vector Quantization

Joseph Chataignon, Stefano Rini

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


A variation of the classic vector quantization problem is considered, in which the analog-to-digital (A2D) conversion is not constrained by the cardinality of the output but rather by the number of comparators available for quantization. More specifically, we consider the scenario in which a vector quantizer of dimension d is comprised of k comparators, each receiving a linear combination of the inputs and producing zero/one when this signal is above/below a threshold. Given a distribution of the inputs and a distortion criterion, the values of the linear combination and threshold are to be configured so as to minimize the distortion between the quantizer input and its reconstruction. This vector quantizer architecture naturally arises in many A2D conversion scenarios in which the quantizer's cost and energy consumption are severely restricted. For this novel vector quantizer architecture, we propose an algorithm to determine the optimal configuration and provide the first performance evaluation for the case of uniform and Gaussian iid sources.

Original languageEnglish
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781728143002
StatePublished - Nov 2019
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: 3 Nov 20196 Nov 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393


Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
Country/TerritoryUnited States
CityPacific Grove


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