The Necessary And Sufficient Condition for Generalized Demixing
Chun-Yen Kuo, Gang-Xuan Lin, Chun-Shien Lu
TL;DR
This paper provides a comprehensive analysis of generalized demixing using convex optimization, offering a new criterion for success and a method to estimate success probability.
Contribution
It introduces a novel success condition for convex-based generalized demixing and applies the approximate kinematic formula to estimate success probability.
Findings
New success criterion for generalized demixing
Method to estimate success probability
Framework applicable to various structured signals
Abstract
Demixing is the problem of identifying multiple structured signals from a superimposed observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. We present a new solution to determine whether or not a specific convex optimization problem built for generalized demixing is successful. This solution will also bring about the possibility to estimate the probability of success by the approximate kinematic formula.
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Taxonomy
TopicsSparse and Compressive Sensing Techniques · Structural Health Monitoring Techniques · Image and Signal Denoising Methods