In this paper, a new scheme of multiresolution recognition of unconstrained handwritten numerals based on dyadic wavelet transform and multilayer cluster neural network is presented.
提出一种基于二进小波变换与多层分组神经网络的自由手写体数字的多分辨率识别算法。
A designing method of wavelet neural network structure based on multiresolution learning is put forward, and the studies of network weights adopt damped least squares.
文章提出一种基于多分辨率学习的正交基小波神经网络结构的设计方法，网络权值的学习采用阻尼递推最小二乘算法。
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