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传感器阵列波束优化设计与应用第二章程序 图8,9，10 ，11，13(Sensor array beam optimization design and application of the second chapter procedures figure8 9 10 11 13)

在matlab环境下系统状态矩阵的编程求法(Under the environment of matlab programming method of the system state matrix)

粒子群算法求解车辆路径优化问题，有需要的可以参考一下(PSO for Vehicle Routing Problem)

说明：  利用冲击响应不变法和双线性不变法设计的巴特沃斯滤波器(Impulse response using the same method and design of the same bilinear Butterworth filter)

Fast Channel Shortening with Polynomial Weighting Functions

Implementation of basic insertion, deletion and search algorithms in a red-black tree in C++.

分别用“m函数 和”simulink 描述了直流有刷电机的控制算法设计。(Respectively m function and simulink describes a DC brush motor control algorithm design.)

sir/mam,,pls prvide me some matlab codes

实序列FFT快速算法，用N点FFT计算2N点实序列的FFT，比直接进行2N点FFT运算减少一半运算量。(Real sequence FFT fast algorithm, using N-point FFT calculation 2N point real sequence of FFT, than the direct 2N-point FFT computation halved.)

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.)