Derivation of centralized and distributed filters using covariance information

The problem of estimating a degraded image using observations acquired from multiple sensors is addressed when the image degradation is modelled by white multiplicative and additive noise. Assuming the state-space model is unknown, the centralized and distributed filtering algorithms are derived usi...

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Veröffentlicht in:	Computational statistics & data analysis 2011, Vol.55 (1), p.312-323
Hauptverfasser:	García-Ligero, M.J., Hermoso-Carazo, A., Linares-Pérez, J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Additives Covariance Exact sciences and technology Filter Filtering Filtration General topics Mathematical analysis Mathematical models Mathematics Multiple sensors Multiplicative noise Multiplicative noise Filter Multiple sensors Multivariate analysis Noise Numerical analysis Numerical analysis. Scientific computation Numerical methods in probability and statistics Probability and statistics Probability theory and stochastic processes Sciences and techniques of general use Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications) Statistics
Online-Zugang:	Volltext
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