dim-pca

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.)

读入ORL人脸库的指定数目的人脸前前五张(训练) 输入：nFacesPerPerson --- 每个人需要读入的样本数，默认值为 5 nPerson --- 需要读入的人数，默认为全部 40 个人 bTest --- bool型的参数。默认为0，表示读入训练样本（前5张）；如果为1，表示读入测试样本（后5张）(Read into the ORL face database face before the specified number of five sheets (Training) Input: nFacesPerPerson--- everyone needs to read the sample size, the default value is 5 nPerson--- the number of people need to read , the default for all 40 individual bTest--- bool type parameters. The default is 0, read the training samples (top 5) If 1, read that the test samples (after 5))

another erett example..

基于MATLAB的批量提取图像的纹理特征，纹理特征提取的方法采用灰度-梯度共生矩阵法。(Extracted texture features based on MATLAB bulk, texture feature extraction method using gray level the- gradient co-occurrence matrix method.)

信号分析与处理中的卷积，适用于合成地震记录(Signal analysis and processing of convolution, for synthetic seismograms)

FX反褶积，matlab程序，用于地震资料处理(FX deconvolution, matlab program for seismic data processing )

超声成像得到的射频信号转换为包络信号时的一维滤波(RF signals into ultrasound imaging to obtain one-dimensional filtering of the envelope signal when)

cyclic autcorrelation AM signal Dsbsc

采用5点3次平滑算法和SG平滑算法对曲线进行平滑处理，结果良好(The curve is smoothed by 5-point 3-order smoothing algorithm and SG smoothing algorithm, and the result is good.)

用matlab开发的系统辩识原代码。利用最小二乘法实现辩识.(Using matlab developed the original system identification code. Realize the use of least squares identification.)