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qiyiyangbenwucha
- 利用感知器和BP网进行模式识别的基本方法，分类线性不可分样本-The basic method of pattern recognition based on perceptron and BP net, the linear non separable sample
pocket-PLA
- 贪婪感知器算法。R语言实现版本，每次会把最优的分类抓在手上-pocket perceptron learning of algorithm
EXP2
- 利用Matlab神经网络工具箱中感知器函数对二维线性可分的样本进行正确分类。-Use Matlab neural network toolbox Perceptron dimensional linearly separable function correctly classified samples.
Perceptron
- 模式识别中的感知器判别准则，实现分类。Matlab源代码-Pattern Recognition Perceptron criterion and achieve classification. Matlab source code
cooc_feature_matrix
- 在holcon中使用多层次感知器对图像进行分类-completeness check of colored game pieces using MLP classification
ANN
- 采用感知器网络实现分类，二维输入，二维输出-Using sensor networks classification, 2D input, 2D output
test
- 使用matlab] 利用神经网络单层感知器 对图像数字二值化进行判断分类 -Use matlab] single-layer perceptron neural network for digital image binarization judgment Categories
preception
- 模式识别的经典算法之一，感知器算法，用来对模式进行分类，采用matlab编写-One of the classic pattern recognition algorithm, perception algorithm, used to classify patterns using matlab prepared
Perceptron
- 本实验的目的是学习和掌握两种感知器算法：批处理感知器算法和批处理裕量松弛 算法。感知器算法是通过学习两类已标记的样本，建立一个线性分类器。学习的过程就是求解感知器权系数的过程，人们通过建立一个准则函数J(a),将求解感知器权系数的问题简化为一个标量函数J(a)的极小化问题，即当a为解向量时，J(a)最小。而极小化问题常用梯度下降法来解决。本实验给出了基于梯度下降法的两种感知器算法，介绍了原理并编程实现，最后对两种算法的特点加以比较分析。-The purpose of this study i
perceptron
- 自己编写的用感知器算法分类UCI数据集中的iris数据集-UCI classification by perception algorithm dataset iris data set
feller
- 一些图像分割中常用的感知器，这些感知器适用于分类的-Some image segmentation is commonly used in the perceptron, these sensors are applied to the classification of
BP-NN-realization-categorizes
- BP网络实现分类问题；一，问题的提出；根据感知器的的相关理论易知感知器善于解决线性可分；反向传播网络（Back-PropagationN；一个具有r个输入和一个隐含层的神经网络模-The BP network realization categorizes a problem A, the problem puts forward Knows a machine according to the feeling of of the related theory easy to underst
perceptron-algorithm-
- 通过感知器算法分类鸢尾花（三类分类），由于感知器算法是二类分类器，所以三类分类需要两两对比。-Classification of iris by perceptron algorithm (three classifications)Since the perceptron algorithm is a class 2 classifier, three classifications require a pairwise comparison.
Perceptron-numerical-experiment
- 1.设计一个单一感知器解决简单分类问题 2.设计多个感知器神经元解决分类问题，并绘出图像 3.利用标准化感知器学习规则消除奇异样本对训练的影响-Design perceptron to solve classification problems
perceptronClustering
- fisher线性分类，多层感知器非线性分类，K-Means聚类-Fisher linear classification, multilayer perceptron linear classifiers, K-Means Clustering
kogt
- 此为BP感知神经分类器,自己写的,有须要的请下载,很不错的,-This is BP neural classifier perception, write their own, have a need to download, very good,
uskr
- 此为BP感知神经分类器,自己写的,有须要的请下载,很不错的,-This is BP neural classifier perception, write their own, have a need to download, very good,
dupa
- 此为BP感知神经分类器,自己写的,有须要的请下载,很不错的,-This is BP neural classifier perception, write their own, have a need to download, very good,
固定增量法求分界面
- 固定增量法求分界面 (利用感知器训练算法中的固定增量法求分界面，将样本集分为两 类)，附带整个分类过程及原理(The fixed increment method calculates the interface (using the fixed increment method in the perceptron training algorithm for the interface, and divides the sample set into two Class))
homework2_2
- 实现批处理感知器算法的程序，用于分类训练集，同时记下收敛时的步数(Program to realize batch perceptron algorithm for classification of training set, and steps to write down the convergence)