a b s t r a c t This paper addresses the reconstruction of sparse vectors in the Multiple Measurement Vectors (MMV) problem in compressive sensing, where the sparse vectors are correlated. This problem has so far been studied using model based and Bayesian methods. In this paper, we propose a deep

The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order

Abstract Large-scale remote sensing images, includ-ing both satellite and aerial photographs, are widely used to render terrain scenes in real-time geographic visualization systems. Such systems often require large memories in order to store fine terrain details and fast network speeds to transfer

nv c, neti me 8, U Sparse representation Non-convex optimization s si the ng W proposed. It has better performance in preserving image edges than conventional sparsifying transforms. are presented in the smooth region when the data are highly undersampled. In RI) is ical str

learning if they trigger deep reflection that leads ultimately to emancipation: the process 'could not be transformative without being challenging, nor could [teachers] own the direction without it being arduous.' Teachers often make sense of such professional learning through the construction

of knowledge and a book in Her lotus hands. Dedicated to the Lotus Feet of the revered Sadguru. This thesis presents a new active mask (AM) framework and an algorithm for segmenta-tion of digital images, particularly those of punctate patterns from fluorescence microscopy. Fluorescence microscopy has greatly

This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable

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Sensor network software update management: a survey By Chih-Chieh Han, Ram Kumar, Roy Shea and Mani Srivastava*,† Software management is a critical task in the system administration of enterprise-scale networks. Enterprise-scale networks that have traditionally comprised of large clusters

de nationalité suisse et originaire de Zurich (ZH) et Lucerne (LU) acceptée sur proposition du jury: