L^2(R^n)空间上的不确定原理

该文主要研究L^2(R^n)空间上的不确定原理,将时频分析中信号的时间和Fourier的频率定义推广到了L^2(R^n)空间上.得到了L^2(R^n)空间上一个更强形式的不确定原理.并得到了不确定原理等式成立的条件.

DENSENESS OF RADIAL-BASIS FUNCTIONS IN L^2(Rn) AND ITS APPLICATIONS IN NEURAL NETWORKS

The authors discuss problems of approximation to functions in L2(Rn) and operators fromL2(Rn1) to L2(Rn2) by Radial-Basis Functions. The results obtained solve the problem ofcapability of RBF neural networks, a basic problem in neural networks.