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ICASSP
2009
IEEE
14 years 1 months ago
Compressive sampling of pulse trains: Spread the spectrum!
In this paper we consider the problem of sampling far below the Nyquist rate signals that are sparse linear superpositions of shifts of a known, potentially wide-band, pulse. This...
Farid M. Naini, Rémi Gribonval, Laurent Jac...
ICASSP
2010
IEEE
13 years 6 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
ICASSP
2010
IEEE
13 years 4 months ago
A sparse component model of source signals and its application to blind source separation
In this paper, we propose a new method of blind source separation (BSS) for music signals. Our method has the following characteristics: 1) the method is a combination of the spar...
Yu Kitano, Hirokazu Kameoka, Yosuke Izumi, Nobutak...
STOC
2002
ACM
96views Algorithms» more  STOC 2002»
14 years 6 months ago
Near-optimal sparse fourier representations via sampling
d Abstract] A. C. Gilbert S. Guhay P. Indykz S. Muthukrishnan M. Strauss We give an algorithm for nding a Fourier representation R of B terms for a given discrete signal A of leng...
Anna C. Gilbert, Sudipto Guha, Piotr Indyk, S. Mut...
ICASSP
2011
IEEE
12 years 10 months ago
Revisiting adaptive least-squares estimation and application to online sparse signal recovery
This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...
Konstantinos Slavakis, Yannis Kopsinis, Sergios Th...