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20092025
most citedSparse sensing and DMD based identification of flow regimes and bifurcations in complex flows

91 citations · 389 across the 28 of their papers we have counts for

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Showing cs.ITShow all

9 papers · 1 filter

cs.IT2021

Multiview Sensing With Unknown Permutations: An Optimal Transport Approach

Yanting Ma, Petros T. Boufounos, Hassan Mansour +1

In several applications, including imaging of deformable objects while in motion, simultaneous localization and mapping, and unlabeled sensing, we encounter the problem of recoveri…

cs.IT2020

Distributed Coding of Quantized Random Projections

Maxim Goukhshtein, Petros T. Boufounos, Toshiaki Koike-Akino +1

In this paper we propose a new framework for distributed source coding of structured sources, such as sparse signals. Our framework capitalizes on recent advances in the theory of…

cs.IT2016★ 4 cited

Cross Validation in Compressive Sensing and its Application of OMP-CV Algorithm

Jinye Zhang, Laming Chen, Petros T. Boufounos +1

Compressive sensing (CS) is a data acquisition technique that measures sparse or compressible signals at a sampling rate lower than their Nyquist rate. Results show that sparse sig…

cs.IT2015

Representation and Coding of Signal Geometry

Petros T Boufounos, Shantanu Rane, Hassan Mansour

Approaches to signal representation and coding theory have traditionally focused on how to best represent signals using parsimonious representations that incur the lowest possible…

cs.IT2014★ 3 cited

Quantization and Compressive Sensing

Petros T. Boufounos, Laurent Jacques, Felix Krahmer +1

Quantization is an essential step in digitizing signals, and, therefore, an indispensable component of any modern acquisition system. This book chapter explores the interaction of…

cs.IT2013★ 19 cited

Robust 1-bit Compressive Sensing via Gradient Support Pursuit

Sohail Bahmani, Petros T. Boufounos, Bhiksha Raj

This paper studies a formulation of 1-bit Compressed Sensing (CS) problem based on the maximum likelihood estimation framework. In order to solve the problem we apply the recently…