Description: Kohonen网络的学习过程可描述为：对于每一个网络的输入，只调整一部分权值，使权向量更接近或更偏离输入矢量，这一调整过程就是竞争学习。随着不断的学习过程，所有输入矢量都在输入矢量空间相互分离，形成了各自代表输入空间的一类模式，这就是Kohonen网络的特征自动识别的聚类功能。请解压缩后按照readme提示进行操作。-Kohonen network learning process can be described as follows : for each one network input, only part of adjusting the weights, weight vector closer to or further from the input vector, the adjustment process is competitive learning. With the continuous process of learning, all the input vector in the importation of vector space separate form their own representatives importation of a type of space, and this is a Kohonen network of automatic clustering functions. Please decompress after readme according to instructions. Platform: |
Size: 2543743 |
Author:尤忠彬 |
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Description: 本算法采用LVQ竞争学习网络，本算法先用分类再用bp算法进行预测。-the algorithm used LVQ competitive learning networks, the algorithm using the classification algorithm reuse bp forecast. Platform: |
Size: 25320 |
Author:keyugang |
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Description: Kohonen 网络模拟大脑神经系统自组织特征映射的功能，它是一种竞争式学习网络，在学习中能无监督地进行自组织学习。-Kohonen network simulation system cerebral self-organizing feature mapping function, It is a competitive learning networks, the study can be carried out without supervision from the organizational learning. Platform: |
Size: 71208 |
Author:东方云 |
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Description: LVQ(学习矢量量化)算法：它是Kohonen的有监督学习的扩展形式。融合了自组织和有导师监督的技术，学习方法是竞争的，但产生方式是有教师监督的，也就是说，竞争学习是在由训练输入指定的各类中局部进行。-LVQ (LVQ) algorithm : it is Kohonen of supervised learning the expansion of the form. The convergence of self-organization and supervision of the instructors, learning methods of competition, but there are ways teachers to supervise, meaning that the competitive learning is the training input from the designated categories of partial. Platform: |
Size: 39769 |
Author:辜小花 |
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Description: LVQ(学习矢量量化)算法：它是Kohonen的有监督学习的扩展形式。融合了自组织和有导师监督的技术，学习方法是竞争的，但产生方式是有教师监督的，也就是说，竞争学习是在由训练输入指定的各类中局部进行。-LVQ (LVQ) algorithm : it is Kohonen of supervised learning the expansion of the form. The convergence of self-organization and supervision of the instructors, learning methods of competition, but there are ways teachers to supervise, meaning that the competitive learning is the training input from the designated categories of partial. Platform: |
Size: 39936 |
Author:辜小花 |
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Description: Kohonen网络的学习过程可描述为：对于每一个网络的输入，只调整一部分权值，使权向量更接近或更偏离输入矢量，这一调整过程就是竞争学习。随着不断的学习过程，所有输入矢量都在输入矢量空间相互分离，形成了各自代表输入空间的一类模式，这就是Kohonen网络的特征自动识别的聚类功能。请解压缩后按照readme提示进行操作。-Kohonen network learning process can be described as follows : for each one network input, only part of adjusting the weights, weight vector closer to or further from the input vector, the adjustment process is competitive learning. With the continuous process of learning, all the input vector in the importation of vector space separate form their own representatives importation of a type of space, and this is a Kohonen network of automatic clustering functions. Please decompress after readme according to instructions. Platform: |
Size: 2543616 |
Author:尤忠彬 |
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Description: 本算法采用LVQ竞争学习网络，本算法先用分类再用bp算法进行预测。-the algorithm used LVQ competitive learning networks, the algorithm using the classification algorithm reuse bp forecast. Platform: |
Size: 363520 |
Author:keyugang |
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Description: Kohonen 网络模拟大脑神经系统自组织特征映射的功能，它是一种竞争式学习网络，在学习中能无监督地进行自组织学习。-Kohonen network simulation system cerebral self-organizing feature mapping function, It is a competitive learning networks, the study can be carried out without supervision from the organizational learning. Platform: |
Size: 70656 |
Author:东方云 |
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Description: LVQ(学习矢量量化)算法：它是Kohonen的有监督学习的扩展形式。融合了自组织和有导师监督的技术，学习方法是竞争的，但产生方式是有教师监督的，也就是说，竞争学习是在由训练输入指定的各类 中局部进行。-LVQ (learning vector quantization) algorithm: it is the Kohonen s supervised the expansion of the form of learning. Blend of self-organization and supervision of technical mentors, learning methods are competitive, but there is a method of supervision of teachers, that is, competitive learning is specified by the training input for various types of local. Platform: |
Size: 36864 |
Author:杨兵 |
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Description: 竞争学习指同一神经元层次上各个神经元相互之间进行竞争，竞争胜利的神经元修改与其相联的连接权值。竞争学习是一种无监督学习。在无监督学习中，只向网络提供一些学习样本，而不提供理想的输出。网络根据输入样本进行自组织，并将其划分到相应的模式类中。
-Competitive learning refers to the same level in all neurons neurons compete with each other, competition victory neuronal modifications associated with its connection weights. Competitive learning is an unsupervised learning. In unsupervised learning, only learning to network with some samples, rather than provide an ideal output. Network in accordance with the importation of samples for self-organization, and its division into the corresponding model class. Platform: |
Size: 2048 |
Author:liyan |
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Description: 竞争学习指同一神经元层次上各个神经元相互之间进行竞争，竞争胜利的神经元修改与其相联的连接权值。竞争学习是一种无监督学习。在无监督学习中，只向网络提供一些学习样本，而不提供理想的输出。网络根据输入样本进行自组织，并将其划分到相应的模式类中。
-Competitive learning refers to the same level in all neurons neurons compete with each other, competition victory neuronal modifications associated with its connection weights. Competitive learning is an unsupervised learning. In unsupervised learning, only learning to network with some samples, rather than provide an ideal output. Network in accordance with the importation of samples for self-organization, and its division into the corresponding model class. Platform: |
Size: 1024 |
Author:于鹏 |
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Description: 本文详细介绍了自分裂竞争学习的方法，适用于竞争学习，神经网络及相关的参考。-This paper describes a self-splitting competitive learning methods, applied to competitive learning, neural network and related reference. Platform: |
Size: 333824 |
Author:Allen |
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Description: 一种通过自组织竞争学习网络实现数据降维和可视化的单层神经网络模型。用此算法可以把输入空间的多维映射到低维的（一维或者二维）的离散网络上，并将保持相同性质的输入数据在映射到低维空间时的拓扑一致性。iris以及letter两个数据集进行分类-A competitive learning through self-organizing network for data dimensionality reduction and visualization of single-layer neural network model. Using this algorithm can be multi-dimensional input space is mapped to the low-dimensional (one-dimensional or two-dimensional) discrete network, and will remain the same as the nature of the input data is mapped to the low-dimensional space of topological consistency. iris as well as the letter the two data sets to classify Platform: |
Size: 1024 |
Author:军军 |
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Description: 基于VC++的Som聚类算法程序。SOM是一种通过自组织竞争学习网络实现数据的分类和降维可视化神经网络模型。内附算法的原理说明以及详细的程序调用说明及运算结果。是初学者的很好的入门材料-Based on VC++ program of Som clustering algorithm. SOM is a competitive learning through self-organizing network for data classification and dimensionality reduction of the visual neural network model. The principle of description included algorithms and detailed description and operation procedures for calling the results. Is a good place to start for beginners Platform: |
Size: 63488 |
Author:xinxin |
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