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In this paper, we consider the source localization for a mixed near-field (NF) and far-field (FF) narrowband signals impinging on a uniform linear array (ULA) with the symmetrical geometric configuration. A computationally efficient direction-of-arrivals (DOAs) and range estimation method for the mixed NF and FF signals is proposed, where the DOAs of the NF and FF signals are estimated separately,...
Computationally efficient source location solutions from TOAs or TDOAs require the squaring of the measurements before optimization. The squaring operation changes the characteristics of the measurements and causes degradation in the localization accuracy, unless proper weightings are applied when forming the cost function for minimization. The previously developed weighting values are useful for...
Principal component analysis (PCA) is a widely used signal processing technique. Instead of performing PCA in the data space, we consider the problem of sparse PCA in a potentially higher dimensional latent space. To do so, we zero-out groups of variables using vector £o regularization. The estimation is based on the maximization of the penalized log-likelihood, for which we develop an efficient coupled...
We introduce a generalization of the MUSIC algorithm to treat block-sparse signals in a multi-measurement vector framework. We show, through theoretical analysis and numerical experiments, that the requirements in terms of number of snapshots and number of measurements depend not only on the sparsity and on the size of the blocks, but also on the rank of the matrices of coefficients for each block...
This work explores performance vs. communication energy tradeoffs in wireless sensor networks that use the recently proposed cutset deployment strategy in which sensors are placed densely along a grid of intersecting lines. For a given number of sensors, intersensor spacing is less for a cutset network than for a conventional lattice deployment, so that cutset networks require less communication energy,...
Acoustic source localization and sound recognition are common acoustic scene analysis tasks that are usually considered separately. In this paper, a new source localization technique is proposed that works jointly with an acoustic event detection system. Given the identities and the end-points of simultaneous sounds, the proposed technique uses the statistical models of those sounds to compute a likelihood...
The objective of brain source imaging consists in reconstructing the cerebral activity everywhere within the brain based on EEG or MEG measurements recorded on the scalp. This requires solving an ill-posed linear inverse problem. In order to restore identifiability, additional hypotheses need to be imposed on the source distribution, giving rise to an impressive number of brain source imaging algorithms...
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