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2015 | OriginalPaper | Buchkapitel

4. Innovations, Wold Decomposition, and Spectral Factorization

verfasst von : Anders Lindquist, Giorgio Picci

Erschienen in: Linear Stochastic Systems

Verlag: Springer Berlin Heidelberg

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Abstract

We begin this chapter by reviewing some basic concepts from the theory of dynamic estimation in the classical setup of Wiener and Kolmogorov. The theory leads naturally to considering certain white noise representations of the observation process, which are prototypes of stochastic dynamical systems described in input-output form. These representations were first introduced in geometric terms in the seminal work of H. Wold on stationary processes and prediction theory. Wold’s ideas have been generalized in many directions. One such generalization will be discussed in this chapter and will form the basis of representation theorems which will be used throughout the book. Generalizations of Wold decomposition have become part of functional analysis and have led to a unifying view of certain fundamental problems in operator theory and Hardy spaces. The operator theoretic (and Hardy space) results which stem from this idea can, in a sense, be seen as function-analytic counterparts of results in the theory of stationary processes and in prediction theory. In Sect. 4.6 we take advantage of this conceptual connection to review, in an economical and essentially self-contained way, some basic parts of Hardy space theory that will be needed in various parts of the book.

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Fußnoten
1
This should be called causally orthonormalizable at this point. The reason for using this new terminology will become clear later on. In the Russian literature, purely nondeterministic processes are called linearly regular.
 
2
A matrix with this property is commonly said to be of full column rank.
 
3
Note that the left inverse is in general non-unique.
 
4
We are here following the engineering convention of taking the complement of the closed unit disc as the region of analyticity.
 
5
To be sure, this is just a corollary of the original Paley-Wiener Theorem, a result of much wider scope than what interests us here.
 
6
Soon we shall prove that this factor is essentially unique and denote it by the symbol W .
 
7
This notation is non-standard. Such functions are called rigid in [104].
 
8
Recall that a real analytic function has poles and zeros which come in conjugate pairs; i.e., α k is a pole (or a zero) if and only if the conjugate \(\bar{\alpha }_{k}\) is also a pole (or a zero). For this reason, either at the numerator or at the denominator of the expression (4.72) α k may be replaced by the conjugate \(\bar{\alpha }_{k}\). Also, in this case there is no need to introduce the convergence factors \(\bar{\alpha }_{k}/\vert \alpha _{k}\vert \) which are needed in the general case [145, p. 64].
 
9
Recall that a square polynomial matrix is unimodular if the inverse is also a polynomial matrix.
 
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Metadaten
Titel
Innovations, Wold Decomposition, and Spectral Factorization
verfasst von
Anders Lindquist
Giorgio Picci
Copyright-Jahr
2015
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-45750-4_4

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