danxiang

代码实现了各种方法的功率谱估计，包括MUSIC,AR,MUDV(Code of the various methods of power spectrum estimation, including MUSIC, AR, MUDV)

英文水印综述性文章1对数字水印的基本介绍和展望(The review of digitalwatermarking 1)

channel equalisation using anfis

自适应算法LMS和rls的MATLAB仿真性能分析(LMS adaptive algorithm and MATLAB simulation performance analysis rls)

K均值算法描述： 给定类的个数K，将N个对象分到K个类中去， 使得类内对象之间的相似性最大，而类之间的相似性最小。(K-means algorithm described: a given number of classes K and N objects assigned to the K-th class, so that objects within the class of the similarity between the maximum, while the similarity between the minimum class.)

单实例运行技术，通过检测互斥对象来实现.Createmutex(run only)

matlab课件，包括7讲，感兴趣的朋友可以看看。(matlab ppt)

Kalman Filtering- Theory and Practice Using MATLAB 2008年第三版的随书源码(Kalman Filtering-Theory and Practice Using MATLAB the third edition CD)

a license plate recognition program easy to understand

The shuffled complex evolution with principal components analysis–University of California at Irvine (SP-UCI) method is a global optimization algorithm designed for high-dimensional and complex problems. It is based on the Shuffled Complex Evolution (SCE-UA) Method (by Dr. Qingyun Duan et al.), but solves a serious problem in searching over high-dimensional spaces," population degeneration". The population degeneration problem refers to the phenomenon that, when searching over the highdimensional parameter spaces, the population of the searching particles is very likely to collapse into a subspace of the parameter space, therefore losing the capability of exploring the entire parameter space. In addition, the SP-UCI method also combines the strength of shuffled complex, the Nelder-Mead simplex, and mutinormal resampling to achieve efficient and effective high-dimensional optimization.