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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Fixed Interval Smoothing for State Space Models

Fixed Interval Smoothing for State Space Models

Weinert, Howard L.

Paperback

Series: The Springer International Engineering and Computer Science, Book 609

Technology & EngineeringGeneral MathematicsProbability & Statistics

ISBN10: 1461356806
ISBN13: 9781461356806
Publisher: Springer Nature
Published: Oct 24 2012
Pages: 119
Weight: 0.43
Height: 0.28 Width: 6.14 Depth: 9.21
Language: English
Fixed-interval smoothing is a method of extracting useful information from inaccurate data. It has been applied to problems in engineering, the physical sciences, and the social sciences, in areas such as control, communications, signal processing, acoustics, geophysics, oceanography, statistics, econometrics, and structural analysis.
This monograph addresses problems for which a linear stochastic state space model is available, in which case the objective is to compute the linear least-squares estimate of the state vector in a fixed interval, using observations previously collected in that interval. The author uses a geometric approach based on the method of complementary models. Using the simplest possible notation, he presents straightforward derivations of the four types of fixed-interval smoothing algorithms, and compares the algorithms in terms of efficiency and applicability. Results show that the best algorithm has received the least attention in the literature.
Fixed Interval Smoothing for State Space Models:
  • includes new material on interpolation, fast square root implementations, and boundary value models;
  • is the first book devoted to smoothing;
  • contains an annotated bibliography of smoothing literature;
  • uses simple notation and clear derivations;
  • compares algorithms from a computational perspective;
  • identifies a best algorithm.
Fixed Interval Smoothing for State Space Models will be the primary source for those wanting to understand and apply fixed-interval smoothing: academics, researchers, and graduate students in control, communications, signal processing, statistics and econometrics.

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