对含噪声数据的一种鲁棒学习算法  

A Robust Learning Algorithm for Noise Data

作　　者：李杰星[1] 章云[1] 符曦[1] 

机构地区：[1]广东工业大学自动化研究所,广州510090

出　　处：《数值计算与计算机应用》2000年第2期112-120,共9页Journal on Numerical Methods and Computer Applications

基　　金：广东省重点学科项目!970003;广东省自然科学基金!960101

摘　　要：llowing for the limitations of LS energy function used in BP algorithm, thispaper proposes a robust learning algorithm based on the study of how cluster-ing puts down radom noise’s effects and the consideration of intensified trainingfor high-quality examples. Some simulation results demonstrate that the robustalgorithm is clearly superior to BP algorithm in anti-disturbance and aJstringency.llowing for the limitations of LS energy function used in BP algorithm, thispaper proposes a robust learning algorithm based on the study of how cluster-ing puts down radom noise's effects and the consideration of intensified trainingfor high-quality examples. Some simulation results demonstrate that the robustalgorithm is clearly superior to BP algorithm in anti-disturbance and aJstringency.

关 键 词：神经网络 鲁棒学习算法 噪声数据 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]