资源列表
kpca081223
- 非线性降维方法KPCA 可以应用于高维数据的机器学习-KPCA nonlinear dimensionality reduction methods can be applied to high-dimensional data, machine learning
GAjulei
- 该程序通过遗传算法对图像进行聚类分析，并实现了图像的分类功能，分类效果明显较其他算法好-The genetic algorithm procedure for cluster analysis of the images and to achieve the classification of image features, the classification results significantly better than the other algorithms
Source_No_GDE_Prob_vs_SNR_ULA
- 该程序用盖氏圆盘方法（GDE）计算均匀直线阵（ULA）中信号源个数估计性能随SNR的变化情况,采用Monte-Carlo模拟。 -estimate the number of source using GDE criterion
Fuzzy-Cluster-Analysis
- 利用VB来实现的模糊聚类分析，形象而且易懂。-The use of VB to achieve the fuzzy cluster analysis, image and easy to understand.
BP_tanh_linaer
- BP神经网络Simulink模型。。例子给了个离散传递函数。训练后的网络可以逼近任意传递函数，或者非线性函数。-Simulink model of BP neural network. . Examples for the discrete transfer function. Trained network can approximate any transfer function, or the nonlinear function.
Demo
- 游戏中的寻路算法C++源码,可以自己编辑地图 。-Wayfinding game algorithm C++ Source, you can edit the map itself.
normal_BP
- LDPC 码的编译码的c语言实现,译码采用的是bp算法,简洁实用-Decoding of LDPC codes c language, decoding algorithm is used in bp, simple and practical
Games
- Bayes分类器——算法设计 1． 使用决策树(Decision tree)分类算法、朴素贝叶斯（Naï ve Bayes）算法或者K-近邻（kNN）算法（三者任选其一）对给定的训练数据集构造分类器，并在测试数据集上进行分类预测。 2． 数据集描述： Tic-tac-toe游戏的二叉分类。Tic-tac-toe游戏示例如下-Bayes classifier- Algorithm 1. Using the decision tree (Decision tree) classi
tentotwo
- 十进制与二进制格雷码的转换——智能计算大作业-Gray code and binary decimal conversion- great job on Intelligent Computing
bys
- 采用贝叶斯正则化算法提高BP网络的推广能力。在本例中，将采用两种训练方法，即L-M优化算法（trainlm)和贝叶斯正则化算法（trainbr),用以训练BP网络，使其能够拟合某一附加有白噪声的正弦样本数据。-The use of Bayesian regularization algorithm for BP network to improve generalization ability. In this case, two types of training methods will b
featureselection
- feature seletion的几篇英文论文 采用pso等进化算法实现特征选取
kmeans
- kmeans文本聚类算法的简单实现，是用JAVA实现的-kmeans a simple realization of the text clustering algorithm is implemented using JAVA