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ICASSP
2011
IEEE
8 years 29 days ago
The value of redundant measurement in compressed sensing
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,...
ICASSP
2011
IEEE
8 years 29 days ago
Improving head-related impulse response measured in noisy environments with spatio-temporal frequency analysis
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...
Takanori Nishino, Kazuya Takeda
ICASSP
2011
IEEE
8 years 29 days ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
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...
Hanchao Qi, Shannon Hughes
ICASSP
2011
IEEE
8 years 29 days ago
Multiple-Measurement Vector model and its application to Through-the-Wall Radar Imaging
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...
ICASSP
2011
IEEE
8 years 29 days ago
Estimation and dynamic updating of time-varying signals with sparse variations
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...
ICASSP
2011
IEEE
8 years 29 days ago
Multi image super resolution using compressed sensing
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...
CORR
2011
Springer
194views Education» more  CORR 2011»
8 years 1 months ago
Sparse approximation property and stable recovery of sparse signals from noisy measurements
—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...
Qiyu Sun
CISS
2011
IEEE
8 years 1 months ago
The Restricted Isometry Property for block diagonal matrices
—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...
TON
2010
113views more  TON 2010»
8 years 3 months ago
Transmit Power Estimation Using Spatially Diverse Measurements Under Wireless Fading
Abstract--Received power measurements at spatially distributed monitors can be usefully exploited to deduce various characteristics of active wireless transmitters. In this paper, ...
Murtaza Zafer, Bongjun Ko, Ivan Wang Hei Ho
TIT
2010
128views Education» more  TIT 2010»
8 years 4 months ago
Shannon-theoretic limits on noisy compressive sampling
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...
Mehmet Akçakaya, Vahid Tarokh
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