Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 2002.07a
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- Pages.26-29
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- 2002
On the Radial Basis Function Networks with the Basis Function of q-Normal Distribution
- Eccyuya, Kotaro (Department of Information & Computer Sciences, Saitama University) ;
- Tanaka, Masaru (Department of Information & Computer Sciences, Saitama University)
- Published : 2002.07.01
Abstract
Radial Basis Function (RBF) networks is known as efficient method in classification problems and function approximation. The basis function of RBF networks is usual adopted normal distribution like the Gaussian function. The output of the Gaussian function has the maximum at the center and decrease as increase the distance from the center. For learning of neural network, the method treating the limited area of input space is sometimes more useful than the method treating the whole of input space. The q-normal distribution is the set of probability density function include the Gaussian function. In this paper, we introduce the RBF networks with the basis function of q-normal distribution and actually approximate a function using the RBF networks.
Keywords