—Hyperspectral unmixing (HU) is a crucial signal processing procedure to identify the underlying materials (or endmembers) and their corresponding proportions (or abundances) fro...
—We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized...
Afsaneh Asaei, Mohammad Javad Taghizadeh, Saeid Ha...
Abstract—Distributed optimization in multi-agent systems under sparsity constraints has recently received a lot of attention. In this paper, we consider the in-network minimizati...
—In this paper, we consider the dictionary learning problem for the sparse analysis model. A novel algorithm is proposed by adapting the simultaneous codeword optimization (SimCO...
Jing Dong, Wenwu Wang, Wei Dai, Mark D. Plumbley, ...
Abstract—We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our alg...
We consider secret-key agreement with public discussion over multiple-input multiple-output (MIMO) Rayleigh fast-fading channels under correlated environment. We assume that trans...
We provide an analysis of a consensus-type algorithm with weights dependent only on the received data. Differently from previous approaches that require a global knowledge of the ...
—Multiscale transforms designed to process analog and discrete-time signals and images cannot be directly applied to analyze high-dimensional data residing on the vertices of a w...
David I. Shuman, Mohammad Javad Faraji, Pierre Van...
Abstract—Most real-world networks exhibit community structure, a phenomenon characterized by existence of node clusters whose intra-edge connectivity is stronger than edge connec...
—We develop a new technique for a dual-function system with joint radar and communication platforms. Sidelobe control of the transmit beamforming in tandem with waveform diversit...
Aboulnasr Hassanien, Moeness G. Amin, Yimin D. Zha...