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Statistical mechanics applied to compressed sensing

Grant number: 14/00792-7
Support Opportunities:Scholarships in Brazil - Doctorate
Start date: July 01, 2014
End date: July 31, 2016
Field of knowledge:Physical Sciences and Mathematics - Physics - General Physics
Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal Investigator:Renato Vicente
Grantee:Paulo Victor Camargo Rossi
Host Institution: Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated scholarship(s):14/22258-2 - Statistical mechanics of 1-bit Compressed Sensing, BE.EP.DR

Abstract

Recent estimates indicate a much faster growth in the production of data compared to the storage capacity and even faster compared to the processing capacity. Compressed Sensing (CS) is a technique that starts from the premise that data acquisition and data compression can occur simultaneously, in a way that extracts the redundancy in the data directly on its acquisition. Methods from Statistical Physics have been broadly used in CS - message passing algorithms were proposed for signal reconstruction and the replica method has proved itself useful in the analysis of the several proposed algorithms. In this project we propose the continuity of the use of techniques from Statistical Mechanics to approach some problems related to CS - among them, the introduction of noise in 1-bit CS, the effect of the use of structured matrices in 1-bit CS, the effect of utilization of source information in Dictionary Learning and CS applications to biological systems and evolutionary dynamics on the measuring matrices. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
ROSSI, PAULO V.; VICENTE, RENATO. L1-Minimization Algorithm for Bayesian Online Compressed Sensing. Entropy, v. 19, n. 12, . (14/00792-7)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
ROSSI, Paulo Victor Camargo. Statistical Physics of Online Compressed Sensing. 2018. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Física (IF/SBI) São Paulo.