Recursive Nonlinear Estimation
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Recursive Nonlinear Estimation: A Geometric Approach(216 Lecture Notes in Control and Information Sciences)

Recursive Nonlinear Estimation: A Geometric Approach(216 Lecture Notes in Control and Information Sciences)


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About the Book

In a close analogy to matching data in Euclidean space, this monograph views parameter estimation as matching of the empirical distribution of data with a model-based distribution. Using a Pythagorean-like geometry of the empirical and model distributions, the book suggests a solution to the problem of recursive estimation of non-Gaussian and nonlinear models which can be regarded as a specific approximation of Bayesian estimation. The cases of independent observations and controlled dynamic systems are considered in parallel; orm er case gives insight into the latter case, which should be of interest to the control community. A number of examples illustrate the key concepts and tools used.

Table of Contents:
Inference under constraints.- From matching data to matching probabilities.- Optimal estimation with compressed data.- Approximate estimation with compressed data.- Numerical implementation.- Concluding remarks.- Selected topics from probability theory.- Selected topics from convex optimization.


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Product Details
  • ISBN-13: 9783540760634
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Publisher Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Height: 235 mm
  • No of Pages: 227
  • Returnable: Y
  • Sub Title: A Geometric Approach
  • ISBN-10: 3540760636
  • Publisher Date: 25 Jun 1996
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Series Title: 216 Lecture Notes in Control and Information Sciences
  • Width: 155 mm


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Recursive Nonlinear Estimation: A Geometric Approach(216 Lecture Notes in Control and Information Sciences)
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