搜索资源列表
LIBSVMsrc
- 一个很好的LIBSVM的JAVA源码。对于要研究和改进SVM算法的学者。可以参考。来自数据挖掘工具YALE工具包。-a good LIBSVM JAVA source. They should study and improve SVM academics. Reference. From Data Mining Tool Kit Yale.
mtpso
- 连续型粒子群算法的java实现，可以自己设计粒子群算法（继承Swarm和Particle类），包含有三个个抽象类（Swarm、Particle、Problem），可以继承Problem类自定义新的问题。-continuous particle swarm algorithm to achieve the java can design their own PSO algorithm (inheritance and Particle Swarm), contains an abstract ca
javasom_1[1].0.0
- 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,
指纹识别c++源程序
- 在vc环境下的指纹识别与处理，我也是从别处得到的，主要看看算法结构。-vc environment in the fingerprint identification and handling, I also received from elsewhere, mainly look at the algorithm.
ImageCodes-Harris
- VC写的harris角点检测程序。又名plessey，最经典也是目前效果最好的算法，比susan抗噪要好（实际的讲）-A program of Harris corner points test writen by VC.We can call is as plessey,it is the best algorithm.It better than susan from real useful point.
pso_2D
- 一种新的优化算法-粒子群算法,优化函数,速度较快,希望大家可以借鉴.-a new optimization algorithm-PSO algorithm optimization function, faster hope we can learn from.
神经网络方法
- 人工神经网络bp 算法是用于数学建模Alife.c 基于遗传算法的人工生命模拟源程序, 输入数据文件world GA_nn.c 基于遗传算法优化神经网络结构源程序,输入数据文件sample Patmat.c 基于遗传算法提取基元图形源序 -bp artificial neural network algorithm is used mathematical modeling based on genetic algorithms Alife.c artificial life simulatio
C45Rule-PANE
- 决策树 C45Rule-PANE算法 解决了决策的问题,是从QUILAN算法修改而成-Decision Tree C45Rule - PANE algorithm to solve the problem of decision-making, from QUILAN algorithm revisions
演化计算(实例-多峰函数最值)
- 演化计算是基于随即搜索的新算法；它的技术模型源于自然的演化。下面是一个例子，该函数是典型的多峰（震动剧烈）的函数。用的算法是郭涛算法。-evolutionary computation is based on the then new search algorithm; It stems from the technical model of the natural evolution. Below is an example of this function is a typical mult
pittnet神经网络源代码
- The purpose of this computer program is to allow the user to construct, train and test differenttypes of artificial neural networks. By implementing the concepts of templates, inheritance andderived classes from C++ object oriented programming, the n
KMeansClustering
- k均值聚类的算法，这是通用程序！欢迎借鉴使用-k average value gathers a kind of algorithm, this is the general routine! Welcome to profit from uses
用Delphi开发的遗传算法源程序
- 开发环境:Delphi 简要说明:TGABase is a abstract class. You must Derivate a sub_class from it. You must override abstract function calculateFitness. By the way, this class can only get minimum solution -development environment : Delphi Brief Descr iption :
决策树c4.5-r8的windows版本
- 用c++实现的决策树算法，windows环境下，希望对学习数据结构和算法的朋友有所帮助。-achieve with the Decision Tree Algorithm, windows environment, and I hope to learn from data structures and algorithms friends help.
c4.5_www2.cs.uregina.ca
- 来自于www2.cs.uregina.ca的c4.5源码-from the Bank www2.cs.uregina.ca FOSS
人脸识别系统设计—毕业设计
- 本课题的主要内容是图像预处理,它主要从摄像头中获取人脸图像然后进行处理,以便提高定位和识别的准确率.该模块主要包含光线补偿、图像灰度化、高斯平滑、均衡直方图、图像对比度增强，图像预处理模块在整个系统中起着极其关键的作用，图像处理的好坏直接影响着后面的定位和识别工作,内有源代码和全部论文资料-this issue is the major content of image preprocessing, mainly from the camera to obtain images Face the
一个fuzzybp训练的程序，值得初学者入门借鉴
- 一个fuzzybp训练的程序，值得初学者入门借鉴-a fuzzybp training procedures, beginners should learn from entry
hopfield解决TSP问题
- 人工神经网络实验之一，用Hopfield网络解决旅行商问题。文件中除源程序外还有word文档对算法，理论，问题描述，实验结果，实验分析的完整介绍-experimental artificial neural network, Hopfield network Traveling Salesman Problem. Apart from the source document but also have a word document of the algorithm theory, and th
my遗传算法
- 该算法实现了神经网络的遗传算法，从简单的角度出发，说明的算法-the algorithm to achieve a neural network genetic algorithm, from the simple point of view that the algorithm
gaByVB
- 遗传算法(Genetic Algorithm, GA)是近几年发展起来的一种崭新的全局优化算法，它借 用了生物遗传学的观点，通过自然选择、遗传、变异等作用机制，实现各个个体的适应性 的提高。-genetic algorithm (Genetic Algorithm, GA) is developed in recent years a new global optimization algorithm, it borrows from the biological point of vi
feature_extraction_face_GE
- An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and genetic algorithm is applied