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 |
Hits:
Description: 自组织 Kohonen 映射程序，当一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。 -Kohonen self-organizing map process, when a neural network to outside input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is done automatically. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method. Platform: |
Size: 3700 |
Author:yybb |
Hits:
Description: 自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ .. Platform: |
Size: 34625 |
Author:张洁 |
Hits:
Description: 开发环境:Matlab 简要说明:自组织特征映射模型(Self-Organizing feature Map)，认为一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method. Platform: |
Size: 731 |
Author:李洋 |
Hits:
Description: 自组织 Kohonen 映射程序，当一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。 -Kohonen self-organizing map process, when a neural network to outside input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is done automatically. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method. Platform: |
Size: 4096 |
Author:yybb |
Hits:
Description: 自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ .. Platform: |
Size: 34816 |
Author:张洁 |
Hits:
Description: 开发环境:Matlab 简要说明:自组织特征映射模型(Self-Organizing feature Map)，认为一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method. Platform: |
Size: 1024 |
Author:李洋 |
Hits:
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 |
Hits:
Description: 自组织神经映射的ＶＣ程序，很好的资源哦
希望大家多多下载-Self-organizing neural VC mapping procedures, good Oh I hope everyone a lot of resources to download Platform: |
Size: 1024 |
Author:jindong |
Hits:
Description: 完全用C++实现的SOM(自组织网络映射)算法，可以用于实际工作和学习中-Entirely in C++ implementation of the SOM (self-organizing network mapping) algorithm, can be used for practical work and learning Platform: |
Size: 55296 |
Author: |
Hits:
Description: 人工神经网络（Artificial Neural Networks，ANN）系统是 20 世纪 40 年代后出现的。它是由众多的神经元可调的连接权值连接而成，具有大规模并行处理、分布式信 息存储、良好的自组织自学习能力等特点。BP（Back Propagation）算法又称为误差 反向传播算法，是人工神经网络中的一种监督式的学习算法。BP 神经网络算法在理 论上可以逼近任意函数，基本的结构由非线性变化单元组成，具有很强的非线性映射能力。(The Artificial Neural Networks (ANN) system appeared after 1940s. It is made up of a number of neurons with adjustable connection weights. It has the characteristics of massively parallel processing, distributed information storage, and good self-organizing and self-learning ability. The BP (Back Propagation) algorithm, also known as the error back propagation algorithm, is a supervised learning algorithm in the artificial neural network. The BP neural network algorithm can approximate any function in theory, and the basic structure is composed of nonlinear change units, and has a strong nonlinear mapping ability.) Platform: |
Size: 4776960 |
Author:songguo2021
|
Hits:
Description: 用自组织映射网络进行聚类分析，然后可以用于颜色识别，图像分割(Clustering analysis using self-organizing mapping network can then be used for color recognition, image segmentation) Platform: |
Size: 69632 |
Author:GG987
|
Hits:
Description: 1981年芬兰 一种自组织特征映射网 ， 又称 Kohonen 网 。 Kohonen 认为 ，一个神经网络接受外界输入模式时， 将会分为不同的对应区域， 各区域对输入模式具有不同的响应特征(In 1981, a self organizing feature mapping network, also known as Kohonen network, was used in Finland. Kohonen thinks that when a neural network accepts external input mode, it will be divided into different corresponding regions. Each region has different response characteristics to input mode.) Platform: |
Size: 46080 |
Author:哼哼1214
|
Hits:
Description: 自组织神经网络概念和原理，并重点介绍一下自组织特征映射SOM网络。SOM和现在流行的ANN（MLP）模型在结构上类似，都由非常简单的神经元结构组成，但是SOM是一类“无监督学习”模型，一般的用法是将高维的input数据在低维的空间表示[1]，因此SOM天然是一种降维方法。除了降维，SOM还可以用于数据可视化，以及聚类等应用中。(The concept and principle of self-organizing neural network are introduced, and the self organizing feature mapping SOM network is introduced. SOM and the now popular ANN (MLP) model is similar in structure, the neuron structure very simple, but SOM is a kind of "unsupervised learning" model, the general is the use of input data with high dimension in the low dimensional space for [1], so SOM is a kind of natural dimensionality reduction method. In addition to dimensionality reduction, SOM can also be used in data visualization, clustering and other applications.) Platform: |
Size: 533504 |
Author:ZJN27 |
Hits:
Description: SOM神经网络也属于自组织型学习网络，只不过更特殊一点它属于自组织特征的映射网络。该网络是由一个全连接的神经元阵列组成的无教师，自组织，自学习的网络。(SOM neural network also belongs to self-organizing learning network, but more specifically, it belongs to self-organizing feature mapping network. The network is a non-teacher, self-organizing, self-learning network composed of a fully connected neuron array.) Platform: |
Size: 48128 |
Author:我们终将遗忘 |
Hits:
Search - self organizing mapping