Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals that enables sampling rates significantly below the classical Nyquist rate. Based on...
Luisa F. Polania, Rafael E. Carrillo, Manuel Blanc...
In this paper, we propose a statistical test to discriminate between original and forged regions in JPEG images, under the hypothesis that the former are doubly compressed while t...
Speech enhancement and separation algorithms frequently employ two-stage processing schemes, where the signal is first mapped to an intermediate low-dimensional parametric descri...
This paper proposes a novel application of image inpainting techniques for the edge enhancement problems in image deblurring and denoising. The edge enhancement effect is achieved...
Acoustic feedback limits the gain provided by hearing aids. Digital hearing aids identify acoustic feedback signals and cancel them continuously in a closed loop with an adaptive ...
Precoding has been extensively studied for point-to-point communications, including the problems of constructing the precoding codebook and selecting the best precoder. This paper...
Yiyue Wu, Haipeng Zheng, A. Robert Calderbank, San...
In this work we describe methods for using the directionality of sound energy as a criterion to estimate single- and multichannel linear filters for suppression of diffuse noise ...
In this paper we discuss why a simple network topology inference algorithm based on network co-occurrence measurements and a Markov random walk model for routing enables perfect t...
In this paper, we create a unified framework for spectrum sensing of signals which have covariance matrices with known eigenvalue multiplicities. We derive the generalized likeli...