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    Algorithms and Theory in Filtering and Control

    Algorithms and Theory in Filtering and Control by Sorensen, Danny C.; Wets, Roger J.-B.;

    Series: Mathematical Programming Studies; 18;

      • GET 8% OFF

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      • Publisher's listprice EUR 84.39
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        35 798 Ft (34 093 Ft + 5% VAT)
      • Discount 8% (cc. 2 864 Ft off)
      • Discounted price 32 934 Ft (31 366 Ft + 5% VAT)

    35 798 Ft

    Availability

    Out of print

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Springer Verlag
    • Date of Publication 1 May 1982
    • Number of Volumes 1 pieces, Book

    • ISBN 9783642008474
    • Binding Hardback
    • No. of pages160 pages
    • Size 0x0 mm
    • Language English
    • 0

    Categories

    Table of Contents:

    The duality between estimation and control from a variational viewpoint: The discrete time case.- The conjugate process in stochastic realization theory.- A Hamiltonian approach to the factorization of the matrix Riccati equation.- On fast computation of superdiagonal Padé fractions.- Stochastic control in discrete time and applications to the theory of production.- Square-root information filtering and smoothing for precision orbit determination.- Some numerical aspects of multivariable systems identification.- Using the Hessenberg decomposition in control theory.- Algorithms for the design of control systems subject to singular value inequalities.- Collinear scaling and sequential estimation in sparse optimization algorithms.

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