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Fixed Interval Smoothing for State Space Models

Name: Fixed Interval Smoothing for State Space Models
Brand: Springer, Berlin
SKU: 9780792372998
Price: 40590 HUF
Availability: InStock

Szerző: Howard L. Weinert

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer, Berlin

Elérhetőség: Beszállítói készleten alacsony példányszámban

Küldés 13-18 napon belül

40 590 Ft

Fixed-interval smoothing is a method of extracting useful information from inaccurate data. It has b...

Információk a könyvről

Szerző

Howard L. Weinert

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2001

oldal

119

EAN

9780792372998

ISBN

0792372999

Enbook ID

04162457

Kiadó

Springer, Berlin

Súly

376

Méretek

160 x 235 x 12

Teljes leírás

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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Fixed Interval Smoothing for State Space Models

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