Radial Basis Functions
Wikipedia English The Free EncyclopediaDownload this dictionary
Radial basis function
A radial basis function (RBF) is a real-valued function whose value depends only on the distance from the origin, so that ; or alternatively on the distance from some other point c, called a center, so that . Any function that satisfies the property is a radial function. The norm is usually Euclidean distance, although other distance functions are also possible. For example by using Lukaszyk-Karmowski metric, it is possible for some radial functions to avoid problems with ill conditioning of the matrix solved to determine coefficients wi (see below), since the is always greater than zero.

See more at Wikipedia.org...


© This article uses material from Wikipedia® and is licensed under the GNU Free Documentation License and under the Creative Commons Attribution-ShareAlike License
Electronic Statistics Textbook DictionaryDownload this dictionary
Radial Basis Functions
A type of neural network employing a hidden layer of radial units and an output layer of linear units , and characterized by reasonably fast training and reasonably compact networks. Introduced by Broomhead and Lowe (1988) and Moody and Darkin (1989), they are described in most good neural network text books (e.g., Bishop, 1995; Haykin, 1994). See, Neural Networks" .


| Radial Basis Functions in French | Radial Basis Functions in Bulgarian