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3 papers · 1 filter
Compressive Matched-Field Processing
William Mantzel, Justin Romberg, Karim Sabra
Source localization by matched-field processing (MFP) generally involves solving a number of computationally intensive partial differential equations. This paper introduces a techn…
Convergence and Rate Analysis of Neural Networks for Sparse Approximation
Aurèle Balavoine, Justin Romberg, Christopher J. Rozell
We present an analysis of the Locally Competitive Algorithm (LCA), a Hopfield-style neural network that efficiently solves sparse approximation problems (e.g., approximating a vect…
Matched Filtering from Limited Frequency Samples
Armin Eftekhari, Justin Romberg, Michael B. Wakin
In this paper, we study a simple correlation-based strategy for estimating the unknown delay and amplitude of a signal based on a small number of noisy, randomly chosen frequency-d…