共 1 条
- [1] Approximation by superpositions of a sigmoidal function[J] . G. Cybenko.Mathematics of Control, Signals and Systems . 1989 (4)
A MULTILAYER COMPLEX NEURAL NETWORK TRAINING ALGORITHM AND ITS APPLICATION IN ADAPTIVE EQUALIZATION
被引：1
作者：
Li Chunguang Liao Xiaofeng Wu Zhongfu Yu Juebang(Dept. of Optoelectronic Technology
机构：
关键词：
Neural network;
Recursive;
Equalization;
D O I：
暂无
中图分类号：
TP183 [人工神经网络与计算];
学科分类号：
081104 ;
0812 ;
0835 ;
1405 ;
摘要：
In this paper, the layer-by-layer optimizing algorithm for training multilayer neural network is extended for the case of a multilayer neural network whose inputs, weights, and activation functions are all complex. The updating of the weights of each layer in the network is based on the recursive least squares method. The performance of the proposed algorithm is demonstrated with application in adaptive complex communication channel equalization.
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页码：321 / 329
页数：9
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