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1289 results found.
Section: Our Story
Pennsylvania State University
University Park, PA, USA
Section: Our Story
Military Institute of Engineering
Brazil
Section: Our Story
University of Illinois at Chicago
Chicago, IL, USA
Section: Our Story
University of Ioannina
Ioannina, Greece
Section: Our Story
National Taiwan University
Taipei, Taiwan
Section: Our Story
University of Hawaii at Manoa
Honolulu, HI, USA
Section: Our Story
Laboratoire Lagrange - UMR
Nice, France
Section: Our Story
Sarvajanik College of Engineering & Technology
Surat, India
Section: Publications & Resources
Expander recovery is an iterative algorithm designed to recover sparse signals measured with binary matrices with linear complexity. In the paper, we study the expander recovery performance of the bipartite graph with girth greater than 4, which can be associated with a binary matrix with column correlations equal to either 0 or 1.
Section: Publications & Resources
We study the problem of distributed filtering for state space models over networks, which aims to collaboratively estimate the states by a network of nodes. Most of existing works on this problem assume that both process and measurement noises are Gaussian and their covariances are known in advance. In some cases, this assumption breaks down and no longer holds.
