Gaussian processes for switching regimes

Amos Storkey

doi:10.1007/978-1-4471-1599-1_94

Gaussian processes for switching regimes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

It has been shown that Gaussian processes are a competitive tool for nonparametric regression and classification. Furthermore they are equivalent to neural networks in the limit of an infinite number of neurons. Here we show that the versatility of Gaussian processes at defining different textural characteristics can be used to recognise different regimes in a signal switching between different sources.

Original language	English
Title of host publication	ICANN 98
Subtitle of host publication	Proceedings of the 8th International Conference on Artificial Neural Networks, Skövde, Sweden, 2–4 September 1998
Publisher	Springer
Pages	621-626
Number of pages	6
ISBN (Electronic)	978-1-4471-1599-1
ISBN (Print)	978-3-540-76263-8
DOIs	https://doi.org/10.1007/978-1-4471-1599-1_94
Publication status	Published - 1998

Publication series

Name	Perspectives in Neural Computing
Publisher	Springer London
ISSN (Print)	1431-6854

Access to Document

10.1007/978-1-4471-1599-1_94

Storkey1998GaussianProcessesforSwitchingRegimes-1Accepted author manuscript, 147 KB

http://link.springer.com/chapter/10.1007/978-1-4471-1599-1_94

Cite this

@inproceedings{813e93ce8abd4d6eadb6f4e794e2783c,

title = "Gaussian processes for switching regimes",

abstract = "It has been shown that Gaussian processes are a competitive tool for nonparametric regression and classification. Furthermore they are equivalent to neural networks in the limit of an infinite number of neurons. Here we show that the versatility of Gaussian processes at defining different textural characteristics can be used to recognise different regimes in a signal switching between different sources.",

author = "Amos Storkey",

year = "1998",

doi = "10.1007/978-1-4471-1599-1_94",

language = "English",

isbn = "978-3-540-76263-8",

series = "Perspectives in Neural Computing",

publisher = "Springer",

pages = "621--626",

booktitle = "ICANN 98",

address = "United Kingdom",

}

TY - GEN

T1 - Gaussian processes for switching regimes

AU - Storkey, Amos

PY - 1998

Y1 - 1998

N2 - It has been shown that Gaussian processes are a competitive tool for nonparametric regression and classification. Furthermore they are equivalent to neural networks in the limit of an infinite number of neurons. Here we show that the versatility of Gaussian processes at defining different textural characteristics can be used to recognise different regimes in a signal switching between different sources.

AB - It has been shown that Gaussian processes are a competitive tool for nonparametric regression and classification. Furthermore they are equivalent to neural networks in the limit of an infinite number of neurons. Here we show that the versatility of Gaussian processes at defining different textural characteristics can be used to recognise different regimes in a signal switching between different sources.

U2 - 10.1007/978-1-4471-1599-1_94

DO - 10.1007/978-1-4471-1599-1_94

M3 - Conference contribution

SN - 978-3-540-76263-8

T3 - Perspectives in Neural Computing

SP - 621

EP - 626

BT - ICANN 98

PB - Springer

ER -

Gaussian processes for switching regimes

Abstract / Description of output

Publication series

Access to Document

Fingerprint

Cite this