MAXIMUM-ENTROPY SIGNAL RECONSTRUCTION WITH NEURAL NETWORKS

被引：22
|
作者：
INGMAN, D
MERLIS, Y
机构：
[1] Department of Quality Assurance and Reliability, Technion Israel Institute of Technology, Haifa
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 1992年 / 3卷 / 02期
关键词：
D O I：
10.1109/72.125860
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper is devoted to implementation of the maximum entropy reconstruction algorithms by means of neural networks. It is shown that the solutions of the maximum entropy problem correspond to the steady states of the appropriate Hopfield net. The choice of network parameters is discussed, and existence of the maximum entropy solution is proved.
引用
收藏
页码：195 / 201
页数：7
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