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Distributions at random events

Podgorski, Krzysztof LU and Rychlik, Igor LU (2016) 2nd International Conference on Event-Based Control, Communication, and Signal Processing, EBCCSP 2016 In 2016 2nd International Conference on Event-Based Control, Communication, and Signal Processing, EBCCSP 2016 - Proceedings
Abstract

We discuss the generalized Rice formula approach to deriving long-run distributions of characteristics defined at random events of a stochastic process or field. The approach stems from the same principle originally introduced by Rice for the level crossing intensity in a random signal and we review its extensions to more general contexts. Events are defined on random surfaces through crossing levels of (multivariate) stochastic fields. We also account for the dynamics of spatial-temporal fields using observed velocities. Extensions beyond the Gaussian model are shown and models for sampling from the level crossing distributions are presented. The importance of these generalizations for applications is illustrated through examples.

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author
organization
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type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2016 2nd International Conference on Event-Based Control, Communication, and Signal Processing, EBCCSP 2016 - Proceedings
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
2nd International Conference on Event-Based Control, Communication, and Signal Processing, EBCCSP 2016
external identifiers
  • scopus:84998611033
ISBN
9781509041961
DOI
10.1109/EBCCSP.2016.7605277
language
English
LU publication?
yes
id
e9caaea8-f26b-4bcd-a37e-2d3d3839f022
date added to LUP
2016-12-20 11:20:35
date last changed
2017-02-02 10:26:00
@inproceedings{e9caaea8-f26b-4bcd-a37e-2d3d3839f022,
  abstract     = {<p>We discuss the generalized Rice formula approach to deriving long-run distributions of characteristics defined at random events of a stochastic process or field. The approach stems from the same principle originally introduced by Rice for the level crossing intensity in a random signal and we review its extensions to more general contexts. Events are defined on random surfaces through crossing levels of (multivariate) stochastic fields. We also account for the dynamics of spatial-temporal fields using observed velocities. Extensions beyond the Gaussian model are shown and models for sampling from the level crossing distributions are presented. The importance of these generalizations for applications is illustrated through examples.</p>},
  author       = {Podgorski, Krzysztof and Rychlik, Igor},
  booktitle    = {2016 2nd International Conference on Event-Based Control, Communication, and Signal Processing, EBCCSP 2016 - Proceedings},
  isbn         = {9781509041961},
  language     = {eng},
  month        = {10},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Distributions at random events},
  url          = {http://dx.doi.org/10.1109/EBCCSP.2016.7605277},
  year         = {2016},
}