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通过matlab编程,建立了基于广义神经网络的数据预测,并通过交叉验证进行网络的训练,取得了不错的预测效果-By matlab programming,we established the data forecasting based on generalized regression neural network, and we use corss-validation to train the network,which obtains better forecasting effect.
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摘要:回顾了神经网络理论发展的历史和现状。在此基础上,介绍并讨论了20世纪如年代神经网络研究的一些新进展。根据神经网络研究的特点,对人工神经网络今后的发展前景作了一定的评述,
人工神经网络的研究与发展必将对现代科学技术产生深远的影响.配准中基于像素和基于特征两类主要方法的优缺点 深入研究了互信息理论在医学图像配准领域的应用和实现机理以及互信息作为相似性测度的优缺点。本文着
重深入研究了Renyi广义互信息及其在图像配准中的作用,并针对互信息计算的复杂性,引入了广义近邻图嫡估计理论,并成功
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该文件是GRNN的数据预测的源代码,可用于基于广义回归神经网络的货运量预测-The file is a the GRNN data predicted source code that can be used for cargo forecast based on generalized regression neural network
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GRNN的数据预测:基于广义回归神经网络货运量预测中的源程序及数据-GRNN data to predict the source program and data forecast generalized regression neural network based on the amount of cargo
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基于人工神经网络的常用数字信号调制,包括邓氏关联度、绝对关联度、斜率关联度、改进绝对关联度,gmcalab 快速广义的形态分量分析。- The commonly used digital signal modulation based on artificial neural network, Including Deng s correlation, absolute correlation, correlation of slope, improved absolute correlatio
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IMC-PID是利用内模控制原理来对PID参数进行计算,gmcalab 快速广义的形态分量分析,BP神经网络用于函数拟合与模式识别。- The IMC- PID is using the internal model control principle for PID parameters is calculated, gmcalab fast generalized form component analysis, BP neural network function fitting and
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毕业设计有用,BP神经网络的整个训练过程,包括广义互相关函数GCC时延估计。- Graduation useful The entire training process BP neural network, Including the generalized cross-correlation function GCC time delay estimation.
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这是第二能量熵的matlab代码,基于人工神经网络的常用数字信号调制,包括广义互相关函数GCC时延估计。- This is the second energy entropy matlab code, The commonly used digital signal modulation based on artificial neural network, Including the generalized cross-correlation function GCC time delay e
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BP神经网络的整个训练过程,gmcalab 快速广义的形态分量分析,是学习PCA特征提取的很好的学习资料。- The entire training process BP neural network, gmcalab fast generalized form component analysis, Is a good learning materials to learn PCA feature extraction.
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针对货运量预测问题,建立广义神经网络,对货运量进行预测。同时建立了BP神经网络,通过预测误差进行比较(Aiming at the problem of freight volume prediction, a generalized neural network is established to predict freight volume. At the same time, a BP neural network is established to compare the predicti
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