Hostname: page-component-848d4c4894-pftt2 Total loading time: 0 Render date: 2024-05-18T07:07:53.911Z Has data issue: false hasContentIssue false

Optimalities for random functions Lee-Wiener’s network and non-canonical representation of stationary Gaussian processes

Published online by Cambridge University Press:  22 January 2016

Win Win Htay*
Affiliation:
Graduate School of Mathematics, Nagoya University, Chikusa-Ku, Nagoya 464-8602, Japan
*
Department of Mathematics, University of Yangon, Yangon, Myanmar
Rights & Permissions [Opens in a new window]

Abstract.

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Representation of a Gaussian process in terms of a Brownian motion is a powerful tool in the investigation of its structure. Among various representations is the canonical representation which is viewed as the best one from the viewpoint of the prediction theory. We have discovered some significance of non-canonical representations and discuss their optimality in an information theoretical approach.

Type
Research Article
Copyright
Copyright © Editorial Board of Nagoya Mathematical Journal 1998

References

[1] Hida, T., Brownian Motion, Springer-Verlag, 1980.Google Scholar
[2] Hida, T. and Hitsuda, M., Gaussian Processes, Amer. Math. Soc. Providence, Rhode Island, 1993.Google Scholar
[3] Hoffman, K., Banach Spaces of Analytic Functions, Prentice-Hall, Inc., 1962.Google Scholar
[4] Ihara, S., Information Theory for Continuous Systems, World Scientific, 1993.Google Scholar
[5] Rozanov, Yu. A., Stationary Random Processes, Holden-Day, 1967.Google Scholar
[6] Hibino, Y., Hitsuda, M. and Muraoka, H., Remarks on a non-canonical representation for a stationary Gaussian process.Google Scholar
[7] Wiener, N., Nonlinear Problems in Random Theory, M.I.T. Press, Second edition, 1963. Graduate School of Mathematics Nagoya University Chikusa-ku, Nagoya 4-64-8602 Japan Google Scholar