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2012 conference paper

Optimal estimation with arbitrary error metrics in compressed sensing

2012 IEEE Statistical Signal Processing Workshop (ssp), 588–591.

By: J. Tan n, D. Carmon n & D. Baron n

topics (OpenAlex): Sparse and Compressive Sensing Techniques; Distributed Sensor Networks and Detection Algorithms; Analog and Mixed-Signal Circuit Design
TL;DR: This paper proposes a simple, fast, and general algorithm that estimates the original signal by minimizing an arbitrary error metric defined by the user, and describes a general method to compute the fundamental information-theoretic performance limit for any well-defined error metric. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

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