ica_matlab

rake接收机仿真，Rake接收机是一种能分离多径信号并有效合并多径信号能量的最终接收机。瑞克接收的过程相当于用一个钉耙将各个多径信号“耙”出来，然后加以收集。(rake receiver simulation, Rake receiver is a multipath signals can be separated and the effective integration of multi-path signal energy of the final receiver. Rick received the equivalent of using a rake to process each multipath signal " rake" out, and then collecting them.)

matlab工作空间中的常用命令简介，浅显易懂()

An implementation of a Nonlinear Bilinear Filter

留一法的matlab源代码，很不错的东西(Leave-one of the matlab source code, it is a good thing)

16qam子空间法盲信道估计和信号恢复 (Legal 16qam subspace channel estimation)

卡尔曼滤波的matlab实现，以以及卡尔曼滤波matlab实现过程中出现问题的解决方法(kalman filter matlab)

SVM（支持向量机）参数寻优代码，可自动实现支持向量机的参数寻优(SVM (support vector machine) parameter optimization code that can automatically support vector machine parameter optimization)

二元三节点拉格朗日插值函数源代码，用于二位数据插值和科学计算，适合学习matlab者参考。(Two yuan three-node Lagrange interpolation function source code for the two data interpolation and scientific computing for learning matlab reference.)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

数据模型归一化，模态振动，包含飞行器飞行中的姿态控制，如侧滑角，倾斜角，滚转角，俯仰角，可以动态调节运行环境的参数。( Normalized data model, modal vibration, It comprises aircraft flight attitude control, such as slip angle, tilt angle, roll angle, pitch angle, Can dynamically adjust the parameters of the operating environment.)