搜索资源列表
psobp
- 该文件是使用粒子群算法来求解BP神经网络饿最优解，进而对样本数据训练学习-The document is the use of particle swarm optimization to solving hunger BP neural network the optimal solution, and then the training sample data for the study
bianyiyuanli
- 编译原理，老师讲课的ppt 很全面 值得很好学习-Compiler Construction Principles, teachers lecture ppt very comprehensive study should be very good
Character_Recognition_Training__NN_for_classificat
- 图像特征识别通过神经网络训练方法实现，是学习参考的好资料-you will need first to run the file that name "charGUI4.fig" and on the right side there is a load training set where you have to train the system first, run any data that is should be from 1 to 9 and 0 like ( 1 2 3 4 5 5
source
- ID3算法实现机器学习和分类，根据训练结果，自动生成可以运行的C++语言代码。-ID3 machine learning algorithm and classification, according to the training results, it can run automatically generated C++ language code.
BP
- 神经网络bp算法VC++实现网络的相关运算有：1、网络的输入输出接口，即训练数据的输入，各层权值和节点阈值的输出；2、网络的学习，包括前向传播运算和反向传播运算，误差估计，权值阈值修改；3、网络预测的实现等等。其中网络的学习算法采用变步长和加动量项的优化学习算法，经过我的实验对网络的学习效率有很大提高-Neural network bp algorithm VC++ to achieve the network-related operations: 1, the network input a
feed-forwardnetwork
- 两级前馈神经网络训练的M文件代码，代码后都有注释，用户只需修改训练条件以及前面需要训练的数据即可，是典型的神经网络，下载后直接复制到M文件即可运行成功！是学习神经网络控制的必备-Two feed-forward neural network training M-file code, code has a comment, users only need to modify the training conditions and the need to train before the data
intellectual
- 探讨了动量系数和学习率自适应调整的神经网络算法, 给出了动量系数和学习率的调整方法, 并作为机械故 障的特征识别方法, 以小波分析技术作为机械故障特征信号的提取手段, 由此建立了基于小波与自适应神经网络 的旋转机械故障智能诊断系统, 给出了诊断系统的训练学习方式和工作方式, 通过实际测试数据的诊断结果说明此诊断系统对故障诊断是有效的。-intelligent dignose it is very useful
rapid-object-detection
- 这个是openCV haar训练学习的参考的文章，对haar学习很有帮助-This is openCV haar training to learn the reference article, very helpful for haar
opencv
- OpenCV训练学习之训练程序剖析 -Learning OpenCV Training Analysis Training Program
C4.5
- 决策树经典学习算法，C4.5算法是ID3算法的改进，加上了子树的信息，因素属性的值可以是连续量,训练例的因素属性值可以是不确定的,对已生成的决策树进行裁剪,减小生成树的规模.-Decision tree learning algorithm of C4.5 algorithm is the classic, the improved ID3 algorithm, coupled with the subtree of the information, the factor attribute v
but_ssdut
- bayes分类器，通过前期依靠样本自身的训练学习实现对信息，数据，图像等的分类判断，分析，处理-bayes classifier, rely on samples through pre-training to learn the judgment on the classification of information, data, images, analysis, processing
7-4
- 归一化LMS算法，自适应滤波研究中的一个小程序。20次训练学习。-Normalized LMS algorithm, Adaptive Filtering in a small program. 20 training and learning.
svm
- 图像处理模式识别一种分类算法：svm，对于所提取的图像的特征进行训练学习然后分类。-Image processing, pattern recognition of a classification algorithm: SVM trained to learn the characteristics of the extracted image and then classified.
FaceTrainPose
- 本代码为机器学习中表情识别算法的实现运用了神经网络方法训练学习模型从而达到表情识别的目的-The code for the machine learning facial expression recognition algorithm, the use of neural networks, the training model of learning so as to achieve the purpose of expression recognition
BP
- 利用BP神经网络拟合三维函数，通过训练学习预测函数输出。-BP neural network fitting three-dimensional function, through training to learn prediction function output.
Handwritten-numeral-recognition
- 为了实现对手写字体的识别，运用了人工智能的分层神经网络思想，对识别的字体通过训练学习，达到识别手写字体的功能。-to realize the recognition of handwritten font, using hierarchical neural network artificial intelligence, to identify fonts through training and learning, to identify the handwriting function.
FOA-ELM
- 算法思想是：1） 根据果蝇优化算法得到极速学习机隐层神经元的数目；2） 依据得到的隐层神经元数目和极限学习机的方法对训练样本和测试样本进行训练学习。只要打开fruitfly_elm.m文件运行即可，可以换数据集 -Algorithm idea is: 1) according to the number of flies speed machine learning algorithm to obtain the hidden layer neurons optimization Method
svm-skills-
- 支持向量机的分类到训练学习的全套示例，程序简单明了，是接触支持向量机最好的入门资料。-Support vector machine (SVM) classification of a full set of sample to study training, procedures simple and clear, is the best introductory material contact with support vector machine (SVM).
NNBP_code_Changed
- 实现多层神经网络算法的源码，并附带训练学习说明，由于程序没有实现归一化功能, 因此用来训练的样本数据首先要归一化后才能进行训练。-实现多层神经网络算法的源码，并附带训练学习说明，由于程序没有实现归一化功能, 因此用来训练的样本数据首先要归一化后才能进行训练。 请键入文字或网站地址，或者上传文档。 取消 Shíxiàn duō céng shénjīng wǎngluò suànfǎ de yuánmǎ, bìng fùdài xùnliàn xuéxí shuōmíng, yóuyú
shibie
- 对预处理及分割之后的图像进行识别 利用BP神经网络进行训练 学习-On after pretreatment and segmentation of image recognition using BP neural network for training study