Diffusion recursive least-squares for distributed estimation over adaptive networks

We study the problem of distributed estimation over adaptive networks where a collection of nodes are required to estimate in a collaborative manner some parameter of interest from their measurements. The centralized solution to the problem uses a fusion center, thus, requiring a large amount of ene...

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Veröffentlicht in:IEEE transactions on signal processing Jg. 56; H. 5; S. 1865 - 1877
Hauptverfasser: Cattivelli, F.S., Lopes, C.G., Sayed, A.H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.05.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Adaptive networks
Adaptive systems
Algorithm design and analysis
Algorithms
Applied sciences
Collaboration
consensus
cooperation
Detection, estimation, filtering, equalization, prediction
Diffusion
distributed estimation
Distributed processing
Estimates
Exact sciences and technology
Information, signal and communications theory
Inversions
Least squares method
Matrices
Network topology
Networks
Performance analysis
Recursive
Recursive estimation
Resonance light scattering
Signal and communications theory
Signal processing algorithms
Signal, noise
Telecommunications and information theory
Time measurement
Performance evaluation
distributed estimation
Parameter estimation
diffusion
Adaptive system
Recursive algorithm
Adaptive networks
consensus
Distributed processing
Least squares method
Recursive method
Communication complexity
cooperation
ISSN:1053-587X, 1941-0476
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Beschreibung
Zusammenfassung:We study the problem of distributed estimation over adaptive networks where a collection of nodes are required to estimate in a collaborative manner some parameter of interest from their measurements. The centralized solution to the problem uses a fusion center, thus, requiring a large amount of energy for communication. Incremental strategies that obtain the global solution have been proposed, but they require the definition of a cycle through the network. We propose a diffusion recursive least-squares algorithm where nodes need to communicate only with their closest neighbors. The algorithm has no topology constraints, and requires no transmission or inversion of matrices, therefore saving in communications and complexity. We show that the algorithm is stable and analyze its performance comparing it to the centralized global solution. We also show how to select the combination weights optimally.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2007.913164