An improved algorithm for image restoration based on modified Hopfield neural network

被引：0

作者：

Wu, YD ^{[1
]}

Chen, YH ^{[1
]}

Zhang, HY ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Engn & Comp Sci, Chengdu 610054, Peoples R China

来源：

Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年

关键词：

image restoration; neural network; sequential algorithm;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The neural network method is widely used in image restoration, since its advantages such as the abilities of parallel computing, nonlinear mapping and self-adaptiveness. In this paper, an improved sequential algorithm is proposed, which uses the modified Hopfield neural network based on continuous state change, and maximal energy descent in the update rule. Experiment results show that the improved sequential algorithm could converge to a stable point with high speed, and give more precise restoration results.

引用

页码：4720 / 4723

页数：4

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