A least-squares quadratic filter and fixed-point smoother from uncertain observations of a signal are derived when the variables describing the uncertainty are nonindependent, and the observations are perturbed by white and coloured noise. The proposed estimators do not require knowledge of the state-space model of the signal; the available information is only the moments, up to the fourth one, of the involved processes, the probability that the signal exists in the observations, and the (2,2)-element of the conditional probability matrix of the sequence describing the uncertainty.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Least-squares quadratic estimators from nonindependent uncertain observations with coloured noise


    Contributors:


    Publication date :

    2003-01-01


    Size :

    298404 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Least-Squares Quadratic Estimators from Non-Independent Uncertain Observations with Coloured Noise

    Nakamori, S. / Caballero-Aguila, R. / Hermoso-Carazo, A. et al. | British Library Conference Proceedings | 2003


    Denoising of multicomponent images using wavelet least-squares estimators

    De Backer, S. / Pizurica, A. / Huysmans, B. et al. | British Library Online Contents | 2008



    Elastic Model Transitions Using Quadratic Inequality Constrained Least Squares

    Orr, J. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2012