The aim of compressed sensing is to recover attributes of sparse signals using very few measurements. Given an overall bit budget for quantization, this paper demonstrates that th...
Victoria Kostina, Marco F. Duarte, Sina Jafarpour,...
A new noise reduction method based on spatio-temporal frequency analysis is proposed that can be applied to head-related impulse response (HRIR), which is an impulse response betw...
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
This paper addresses the problem of Through-the-Wall Radar Imaging (TWRI) using the Multiple-Measurement Vector (MMV) compressive sensing model. TWR image formation is reformulate...
Jie Yang, Abdesselam Bouzerdoum, Fok Hing Chi Tivi...
This paper presents an algorithm for an 1-regularized Kalman filter. Given observations of a discrete-time linear dynamical system with sparse errors in the state evolution, we e...
Muhammad Salman Asif, Adam Charles, Justin K. Romb...
In this paper we present a new compressed sensing model and reconstruction method for multi-detector signal acquisition. We extend the concept of the famous single-pixel camera to...
Torsten Edeler, Kevin Ohliger, Stephan Hussmann, A...
—In this paper, we introduce a sparse approximation property of order s for a measurement matrix A: xs 2 ≤ D Ax 2 + β σs(x) √ s for all x, where xs is the best s-sparse app...
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...
Han Lun Yap, Armin Eftekhari, Michael B. Wakin, Ch...
Abstract--Received power measurements at spatially distributed monitors can be usefully exploited to deduce various characteristics of active wireless transmitters. In this paper, ...
In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...