NANAOCMay 4, 2018

Regularization of ill-posed problems with non-negative solutions

arXiv:1805.0172210 citationsh-index: 35
Originality Synthesis-oriented
AI Analysis

It provides a comprehensive overview for researchers working on inverse problems requiring non-negative solutions, but is incremental as it surveys existing methods without presenting new results.

This survey reviews variational and iterative methods for reconstructing non-negative solutions of ill-posed problems in infinite-dimensional spaces, summarizing known results and identifying open problems.

This survey reviews variational and iterative methods for reconstructing non-negative solutions of ill-posed problems in infinite-dimensional spaces. We focus on two classes of methods: variational methods based on entropy-minimization or constraints, and iterative methods involving projections or non-negativity-preserving multiplicative updates. We summarize known results and point out some open problems.

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