Shapiai, Mohd. Ibrahim and Ibrahim, Zuwairie and Khalid, Marzuki and Jau, L. W. and Pavlovich, V.
(2011)
*Enhanced Nadaraya-Watson kernel regression: surface approximation for extremely small samples.*
In:
Proceedings - AMS 2011: Asia Modelling Symposium 2011 - 5th Asia International Conference on Mathematical Modelling and Computer Simulation.
IEEE Explorer, USA, pp. 7-12.
ISBN 978-076954414-4

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1109/AMS.2011.13

## Abstract

The function approximation problem is to find the appropriate relationship between a dependent and independent variable(s). Function approximation algorithms generally require sufficient samples to approximate a function. Insufficient samples may cause any approximation algorithm to result in unsatisfactory predictions. To solve this problem, a function approximation algorithm called Weighted Kernel Regression (WKR), which is based on Nadaraya-Watson kernel regression, is proposed. In the proposed framework, the original Nadaraya-Watson kernel regression algorithm is enhanced by expressing the observed samples in a square kernel matrix. The WKR is trained to estimate the weight for the testing phase. The weight is estimated iteratively and is governed by the error function to find a good approximation model. Two experiments are conducted to show the capability of the WKR. The results show that the proposed WKR model is effective in cases where the target surface function is non-linear and the given training sample is small. The performance of the WKR is also compared with other existing function approximation algorithms, such as artificial neural networks (ANN).

Item Type: | Book Section |
---|---|

Uncontrolled Keywords: | non-linear surface function, small samples, weighted kernel regression |

Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |

Divisions: | Electrical Engineering |

ID Code: | 29648 |

Deposited By: | Liza Porijo |

Deposited On: | 21 Mar 2013 06:18 |

Last Modified: | 05 Feb 2017 00:01 |

Repository Staff Only: item control page