gelfigureanaly

针对SVM法线特征筛选算法仅考虑法线对特征筛选的贡献,而忽略了特征分布对特征筛选的贡献的不足,在对SVM法线算法进行分析的基础上,基于特征在正、负例中出现概率的不同提出了加权SVM法线算法,该算法考虑到了法线和特征的分布.通过试验可以看出,在使用较小的特征空间时,与SVM法线算法和信息增益算法相比,加权SVM法线算法具有更好的特征筛选性能.(Normal feature selection for SVM algorithm only considered normal for the contribution of feature selection, to the neglect of the characteristics of the distribution of feature selection have contributed to the lack of normal SVM algorithm based on the analysis, based on the characteristics of the positive and negative cases emergence of a different probability-weighted normal SVM algorithm, which takes into account the distribution and characteristics of normal. through the test can be seen in the use of smaller feature space, the normal and the SVM algorithm and information gain algorithm, normal weighted SVM algorithm has better performance of feature selection.)

说明：  边缘检测的源代码。包括sobel prewitt roberts marr canny的。值得下载！(The source code for edge detection. Including sobel prewitt roberts marr canny' s. Worth downloading!)

主要用蚁群算法用matlab实现，解决城市之间最短路径问题(Ant colony algorithm to achieve the TSP)

Support Vector Machine ToolBOX for MatLAB

使用C 语言编制Mex算法程序，对于提高算法的性能有很大帮助。 希望该文档能帮助大家进入matlab 和 c 语言之间互动的世界，也期待你编制更多的原创程 序奉献给研学论坛，尤其是混沌和分形版面(The use of C language algorithm Mex procedures, for improving the algorithm performance of much help. I hope the document will help us to enter the matlab and c language of interaction between the world, and also look forward to your program to produce more original Forum dedicated to research, especially the chaotic and fractal layout)

通信系统中关于MATLAB的仿真和应用方面的知识，很实用的资料(Communication system simulation on MATLAB and application of knowledge, it is useful information)

讲了卡尔慢滤波的跟踪程序 主要使用目标跟踪的(function kalman)

matlab模拟高斯光束在自由空间的传播轨迹(Gaussian Beam Optics )

运用最小均方误差方法实现波束形成，包括均匀直线阵和平面阵(Using the minimum mean square error method to achieve beamforming, including the uniform linear array and planar array.)

田纳西伊—斯特曼过程是一个基于真实化工生产过程模型。它的数据在许多领域被广泛研究和应用，比如优化控制、过程监控和故障诊断等。(The tennessee-sterman process is based on a real chemical process model.Its data is widely studied and applied in many fields, such as optimal control, process monitoring and fault diagnosis.)