On Random Construction of a Bipolar Sensing Matrix with Compact Representation
Tadashi Wadayama
TL;DR
This paper introduces a method to construct bipolar sensing matrices using binary linear codes and analyzes their RIP properties through ensemble average weight distribution, contributing to compressed sensing theory.
Contribution
It presents a novel random construction of bipolar sensing matrices based on binary linear codes and analyzes their RIP properties.
Findings
Proposes a new bipolar sensing matrix construction method.
Analyzes RIP using ensemble average weight distribution.
Provides theoretical insights into matrix properties.
Abstract
A random construction of bipolar sensing matrices based on binary linear codes is introduced and its RIP (Restricted Isometry Property) is analyzed based on an argument on the ensemble average of the weight distribution of binary linear codes.
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