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Discretization of Parametrizable Signal Manifolds
Elif Vural, Pascal Frossard
Transformation-invariant analysis of signals often requires the computation of the distance from a test pattern to a transformation manifold. In particular, the estimation of the d…
Approximate Decoding Approaches for Network Coded Correlated Data
Hyunggon Park, Nikolaos Thomos, Pascal Frossard
This paper considers a framework where data from correlated sources are transmitted with help of network coding in ad-hoc network topologies. The correlated data are encoded indepe…
Correlation-aware Resource Allocation in Multi-Cell Networks
Dorna Bandari, Gregory Pottie, Pascal Frossard
We propose a cross-layer strategy for resource allocation between spatially correlated sources in the uplink of multi-cell FDMA networks. Our objective is to find the optimum power…
Learning Smooth Pattern Transformation Manifolds
Elif Vural, Pascal Frossard
Manifold models provide low-dimensional representations that are useful for processing and analyzing data in a transformation-invariant way. In this paper, we study the problem of…
Markov Decision Process Based Energy-Efficient On-Line Scheduling for Slice-Parallel Video Decoders on Multicore Systems
Nicholas Mastronarde, Karim Kanoun, David Atienza +2
We consider the problem of energy-efficient on-line scheduling for slice-parallel video decoders on multicore systems. We assume that each of the processors are Dynamic Voltage Fre…
Distributed Representation of Geometrically Correlated Images with Compressed Linear Measurements
Vijayaraghavan Thirumalai, Pascal Frossard
This paper addresses the problem of distributed coding of images whose correlation is driven by the motion of objects or positioning of the vision sensors. It concentrates on the p…