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Description: 介绍了神经网络模式识别的基本知识，适合于模式识别领域的人员-it introduces the ABC of the pattern recognation of NN, it is for the people of pattern recognation
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Size: 554683 |
Author: 黄豪杰 |
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Description: 《神经网络模式识别系统理论》希望对学习神经网络有所帮助-"Pattern Recognition System neural network theory" I hope to learn some help neural network
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Size: 5733737 |
Author: 范鲁明 |
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Description: 《神经网络模式识别及其实现》源程序-"pattern recognition and neural network to achieve" source
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Size: 557890 |
Author: 吴迎笑 |
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Description: 《神经网络模式识别及其实现》源程序,收集了各种神经网络分类的算法《神经网络模式识别及其实现》源程序,收集了各种神经网络分类的算法
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Author: jingyu220@163.com |
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Description: BP神经网络模式识别、函数拟合BP神经网络模式识别、函数拟合BP神经网络模式识别、函数拟合
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Author: zkaychen |
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Description: 《神经网络模式识别及其实现》源程序-"pattern recognition and neural network to achieve" source
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Size: 558080 |
Author: 吴迎笑 |
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Description: 神经网络法实现数字识别。《VC模式识别》源码。-neural network digital identification. "VC pattern recognition" source.
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Author: 刘岩 |
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Description: 基与多种智能方法和模式识别技术的研究,如果你也在从事相关研究,一定要看看,我想应该有借鉴价值-base with a variety of intelligent methods and pattern recognition techniques, but if you are engaged in related research, we must look at, I think there should be a reference value
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Author: 郭小波 |
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Author: 黄豪杰 |
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Description: 开发环境:C++
简要说明:这程序是《神经网络模式识别及其实现》（Pattern Recognition with Neural Networks in C++)美Abhijit S. Pandya等著电子工业出版社1999年6月，书号ISBN 7-5053-5088-9的第九章<神经联想记忆和Hopfield网络>附的程序。-development environments : C Brief Description : This is "pattern recognition and neural network to achieve" (Pattern Recognition with Neural Networks in C) US Abhijit S. Pandya waiting for the electronic publishing industry in June 1999, ISBN 7-5053-5088-9 the ISBN IX lt; associative memory and neural Hopfield network gt; attached procedures.
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Author: 刘华 |
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Description: 神经网络模式识别及其实现，第四章。
内含：ALOPEX和BACKPROP程序。-pattern recognition and neural network to achieve, the fourth chapter. Intron : ALOPEX BACKPROP and procedures.
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Size: 221184 |
Author: 五专 |
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Description: 神经网络模式识别及其实现，第九章。
内含：HOPFIELD和LAM -pattern recognition and neural network to achieve, chap. Intron : LAM and HOPFILED
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Size: 63488 |
Author: 五专 |
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Description: 《神经网络设计》的电子版，主要介绍了神经网络的基本结构和学习规则，重点是对这些神经网络的数学分析、训练方法和神经网络在模式识别、信号处理以及控制系统等工程实践问题中的应用。-"neural network design," The electronic version, introduced a neural network to learn the basic structure and rules, the focus is on neural network analysis, training methods and neural networks in pattern recognition, signal processing and control system engineering practices in the application.
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Size: 6696960 |
Author: 何琦 |
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Description: 《神经网络模式识别系统理论》希望对学习神经网络有所帮助-"Pattern Recognition System neural network theory" I hope to learn some help neural network
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Size: 5733376 |
Author: 范鲁明 |
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Description: 模式识别方面的，挺多的，而且很不错的，下了就知道-of pattern recognition, both sport and it is very good, under the know
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Size: 578560 |
Author: 张庆阳 |
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Description: CPLD的程序，用住于虚心的学习神经网络模式识别及其实现-CPLD procedures used to live modestly in the learning neural network and pattern recognition to achieve
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Author: 李翔 |
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Description: 这是一些有关《神经网络模式识别及其实现》的源程序 比较经典，有很大的参考价值-This the "pattern recognition and neural network to achieve" classic comparison of the source, a great reference value
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Author: 小熊 |
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Description: vc++神经网络模式识别，还可以，对需要做这方面的人比较有用-vc neural network pattern recognition, but also to be done in this area were more useful
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Size: 566272 |
Author: 朱奇俊 |
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Description: 论文标题:自适应模糊系统在手写体数字识别中的应用研究
作者:张镭
作者专业:计算机软件人工智能
导师姓名:黄战
授予学位:硕士
授予单位:暨南大学
授予学位时间:19990501
论文页数:59页
文摘语种:中文文摘
分类号:TP18 TP391.4
关键词:手写体数字 自适应 模糊逻辑 神经网络 模式识别
摘要:该文针对模式识别的特点,构造了适合于模式识别问题的自适应模糊系统,对三种不同学习算法加以改进,在手写全数字识别上对分类器进行了实现,并与采用BP算法训练的三层前馈神经网络分类器相比较,分析其优劣.仿真实验表明,在该文的样本集条件下,自适应模糊分类吕的识别性能优于神经网络分类器,这充分体现了自适应模糊技术用于数字识别的优越性和潜力.-thesis entitled : adaptive fuzzy system in a handwritten numeral recognition of applied research Author : Zhang Lei professional author : artificial intelligence computer software instructor Name : Huang war conferred degrees : Master award units : Jinan University conferred degrees : 19990501 page thesis : Abstracts 59 languages : Chinese Digest Key words : TP18-image Keywords : handwritten digital adaptive fuzzy logic neural network pattern recognition Abstract : In this paper the characteristics of pattern recognition, suitable for the construction of adaptive pattern recognition fuzzy systems, three different learning algorithm to improve the handwriting recognition on digital classification of the device to achieve, BP and with a three-tiered training algorithm for neural network clas
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Author: 成东 |
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