• Near-Optimal Sensor Placement...

Treffer: Near-Optimal Sensor Placement for Linear Inverse Problems

Title:
Near-Optimal Sensor Placement for Linear Inverse Problems
Authors:
RANIERI, Juri, CHEBIRA, Amina, VETTERLI, Martin
Source:
IEEE transactions on signal processing. 62(5-8):1135-1146
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2014.
Publication Year:
2014
Physical Description:
print, 35 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Algorithme glouton, Greedy algorithm, Algoritmo glotón, Capteur mesure, Measurement sensor, Captador medida, Complexité calcul, Computational complexity, Complejidad computación, Conception optimale, Optimal design, Concepción optimal, Erreur quadratique moyenne, Mean square error, Error medio cuadrático, Estimation paramètre, Parameter estimation, Estimación parámetro, Etat actuel, State of the art, Estado actual, Evaluation performance, Performance evaluation, Evaluación prestación, Fonction coût, Cost function, Función coste, Méthode combinatoire, Combinatorial method, Método combinatorio, Optimisation, Optimization, Optimización, Orthogonalité, Orthogonality, Ortogonalidad, Positionnement, Positioning, Posicionamiento, Problème inverse, Inverse problem, Problema inverso, Traitement signal, Signal processing, Procesamiento señal, Frame potential, greedy algorithm, inverse problem, sensor placement
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland
ISSN:
1053-587X
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28403640
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.28403640
Database:
PASCAL Archive

Weitere Informationen

A classic problem is the estimation of a set of parameters from measurements collected by only a few sensors. The number of sensors is often limited by physical or economical constraints and their placement is of fundamental importance to obtain accurate estimates. Unfortunately, the selection of the optimal sensor locations is intrinsically combinatorial and the available approximation algorithms are not guaranteed to generate good solutions in all cases of interest. We propose FrameSense, a greedy algorithm for the selection of optimal sensor locations. The core cost function of the algorithm is the frame potential, a scalar property of matrices that measures the orthogonality of its rows. Notably, FrameSense is the first algorithm that is near-optimal in terms of mean square error, meaning that its solution is always guaranteed to be close to the optimal one. Moreover, we show with an extensive set of numerical experiments that FrameSense achieves state-of-the-art performance while having the lowest computational cost, when compared to other greedy methods.