fang-cheng-qiu-gen

SVM分类器，用于对多维采样点进行分类。可根据类别数修改分类器，我们的模式识别作业。(SVM classifier, multi-dimensional sampling points used for classification. Can be modified according to the number of classification categories, and our pattern recognition operation.)

用matlab编的 找二值图像的重心 可以下下来看看(Made use of the matlab binary image to find the center of gravity can be down to see the next)

说明：  实现了DCT的算法，用Matlab实现了任意维图像的DCT变换问题。(DCT algorithm implemented using Matlab implementation of arbitrary-dimensional DCT-image problems.)

This is a Random Sequence generator used in Cryptography, Spread Spectrum, Information Security

本段matlab程序主要是娱乐性质的，功能是用这些代码运行后会有演奏卡农的效果，非常的神奇，时候MATLAB高手研究。(This paragraph matlab program of entertainment nature, functions will be played after the code is running Canon is very magical, when MATLAB master research.)

基于Matlab的最小二乘支持向量机的工具箱及其应用_李方方(The least squares support vector machine (SVM) based on Matlab toolbox and its application _ Li Fangfang)

EMD分解和小波重构的一些程序。。。。。。。。。。(EMD wavelet decomposition and reconstruction of some programs. . . . . . . . . .)

上传一个word档的联邦式扩展卡尔曼粒子滤波算法，大家学习粒子滤波有益，为了使联邦滤波器够有效处理非高斯、非线性系统的状态估计问题，提出将扩展卡尔曼粒子滤波引入联邦滤波结构中，得到一种新的联邦式扩展卡尔曼粒子滤波算法.使用扩展卡尔曼粒子滤波对联邦滤波子系统的多源数据进行处理，从而摆脱了经典卡尔曼滤波的限制，拓宽了联邦滤波器的实际应用范围.将联邦式扩展卡尔曼粒子滤波算法应用于非线性滤波器的一个标准验证模型进行了仿真实验，结果表明该算法是有效性的.(Abstract: A new particle filter(Federated Extend Kalman Particle Filter，EKF-FPF) is proposed to estimate the state of Non-Gaussian and Non-Linear system for federated filter, in which extend kalman particle filer is introduced to federated filter so that the information fusion of subsystem can be solved by the non-gaussian and non-linear filer. By doing so, the federated filter can get rid of the disadvantage of the ordinary kalman filter to extend its application field. The simulation results of the standard testing model demonstrate the feasibility of the proposed algorithm.)

一个左手介质的FDTD的分析，采用ADE方法离散(A left-handed medium, the analysis of the FDTD method discrete ADE )

数值分析---计算实习题第五章：高斯求积公式(Numerical analysis--- calculation practice problems Chapter: Gaussian quadrature)