资源列表
基于多传感器的神经网络模式识别方法
- 基与多种智能方法和模式识别技术的研究,如果你也在从事相关研究,一定要看看,我想应该有借鉴价值-base with a variety of intelligent methods and pattern recognition techniques, but if you are engaged in related research, we must look at, I think there should be a reference value
[转载]nlogn的最长子序列算法
- 关于用nlogn的最长子序列算法，在网上摘录的-discusses the use of the longest sequences algorithm, in the extract from the Internet
属性相似度的云分类器
- matlab环境下，基于云模型的分类器，包括基于例子群优化的云分类器，和属性相似度云分类器。-Matlab environment, based on cloud model for the classification, including examples Swarm Optimization Based on the cloud classifier, and attribute similarity cloud classifier.
TSP和野人过河
- 货郎担问题和野人过河问题，解压后有word文档，里面有详细说明-traveling salesman problem and savage river, unpacked a word document, containing details
iriscloud
- 云分类器，一种基于云模型理论的分类程序。程序中使用云分类器对Iris数据集进行了测试-cloud classifier, a theoretical model based on cloud classification procedure. Procedures used for cloud classification of Iris data set for testing
3dbeam_stiffness
- 用matlab编写的，有限元三维梁单元的单元刚度矩阵计算程序，各节点6个自由度。-prepared by the three-dimensional finite element beam element of the element stiffness matrix calculation program, the 6-DOF nodes.
NNDemo2.0
- 是一个用MATLAB编的一个系统，是关于各个神经我网络模型和支持向量机的软件包-using MATLAB is a part of a system of various neural network model and I support vector machine packages
单根牛顿切线法2
- 我们的作业 计算方法里面的牛顿切线法求根，（单根情况）。-our operations inside the calculation method Newton tangent Root, (single).
Gauss消元法----不选主元
- 我们的计算方法作业 线性方程组的Gauss消元法（不选主元法）算法实现-our method of calculating operating linear equations Gauss elimination method (Pivot) Algorithm
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.
VC野人八数码程序
- 用VC编制的集成的野人和八数码演示程序。其中野人程序用动态的效果演示，并能设置进度。八数码程序能根据给出的源状态转换成目标状态。-VC establishment of integrated Savage and eight digital presentations. Savage procedures which use dynamic demonstration effect, and can be programmed to progress. Eight digital process
人工神经网络原理及仿真实例
- 该系统使用极其简便，即使 你对各种网络模型不是很深刻的了解，也可以很好的使用该系统。使用时， 你可以自己修改网络的各种参数，交互性较好，而且该系统通过大量的图示 及参数设置，可以让你了解每个应用实例实现的过程及详细步骤。-The system is extremely easy to use, even if you have to various network model is not very profound understanding can be a good use of the