Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering

A chaotic prediction algorithm using a new cost function

Authors
Yun Bu, Wan Xin Kang
Corresponding Author
Yun Bu
Available Online March 2013.
DOI
https://doi.org/10.2991/iccsee.2013.126How to use a DOI?
Keywords
Chaotic time series, density function, cost function, negentropy
Abstract
The traditional cost function, minimization mean square prediction error is not a proper cost function in chaotic series prediction, for many chaotic signals are non-Gaussian distributions. Then we present using minimization error negentropy as new cost function, and derive the nonlinear approximation method. In simulation, the algorithm shows an enhanced performance to a common two order Volterra prediction.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
978-90-78677-61-1
DOI
https://doi.org/10.2991/iccsee.2013.126How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yun Bu
AU  - Wan Xin Kang
PY  - 2013/03
DA  - 2013/03
TI  - A chaotic prediction algorithm using a new cost function
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iccsee.2013.126
DO  - https://doi.org/10.2991/iccsee.2013.126
ID  - Bu2013/03
ER  -