| 联想记忆网络及其在刀具磨损量监测中的应用 |
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| 引用本文： | 高宏力,许明恒,傅攀.联想记忆网络及其在刀具磨损量监测中的应用[J].组合机床与自动化加工技术,2005(2):76-78. |
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| 作者姓名： | 高宏力 许明恒 傅攀 |
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| 作者单位： | 西南交通大学,机械工程学院,成都,610031 |
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| 摘 要： | 文章介绍了联想记忆网络的基本概念、组成特点及其在刀具磨损监测中的应用,详细分析了一种格构联想记忆网络-B样条模糊神经网络的结构和算法.研究表明,应用B样条模糊神经网络构造的刀具磨损量监测系统,与BP型前馈神经网络相比,具有训练时间短,拟合精度高,局部推广能力强等特点,有较高的工程应用推广价值.
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| 关 键 词： | 联想记忆 神经网络 B样条 局部推广 刀具磨损 |
| 文章编号： | 1001-2265(2005)02-0076-03 |
| 修稿时间： | 2004年7月14日 |
Associative Memory Networks and Its Application for Tool Wear Monitoring |
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| GAO Hong-li,XU Ming-heng,FU Pan.Associative Memory Networks and Its Application for Tool Wear Monitoring[J].Modular Machine Tool & Automatic Manufacturing Technique,2005(2):76-78. |
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| Authors: | GAO Hong-li XU Ming-heng FU Pan |
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| Abstract: | The basic concepts and structural features of Associative Memory Networks as well as its application for tool wear monitoring are introduced in this paper. The structure and learning algorithms of B-spline networks which belong to Lattice-Based Associative Memory Networks are analyzed detailedly. Compared with feed forward back propagation neural networks, the study shows that the tool wear monitoring system based on B-spline networks is provided with the characteristic of rapid learning, high accuracy, local generalization ability and high available practicality. |
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| Keywords: | associative memory neural networks B-spline local generalization tool wear |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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