|
个人信息Personal Information
教授
博士生导师
硕士生导师
性别：男
毕业院校：英国牛津大学数学所
学位：博士
所在单位：数学科学学院
学科：计算数学
电子邮箱：wuweiw@dlut.edu.cn
扫描关注
L(p) approximation capability of RBF neural networks
点击次数：
论文类型：期刊论文
发表时间：2008-09-01
发表刊物：ACTA MATHEMATICA SINICA-ENGLISH SERIES
收录刊物：ISTIC、CSCD、SCIE、Scopus
卷号：24
期号：9
页面范围：1533-1540
ISSN号：1439-8516
关键字：neural networks; radial basis function; L(p) approximation capability
摘要：L(p) approximation capability of radial basis Function (RBF) neural networks is investigated. If g : R(+)(1) -> R(1) and g(parallel to x parallel to(n)(R)) epsilon L(loc)(p)(R(n)) with 1 <= p <= infinity, then the RBF neural networks with g as the activation function can approximate any given function in LP(K) with any accuracy for any compact set K in R(n), if and only if g(x) is not an even polynomial.