DYNT

这是一个普通的、容易理解的卡尔曼跟踪滤波器的程序，对初学者有较大的帮助(This is a common, easy to understand the procedure of the Kalman tracking filter, a great help for beginners)

用matlab实现粒子滤波算法 x = 0 初始状态 R = input( 请输入过程噪声方差R的值: ) 测量噪声协方差 Q = input( 请输入观测噪声方差Q的值: ) 过程状态协方差 tf = 100 模拟长度 N = 100 粒子滤波器中的粒子个数 xhat = x P = 2 xhatPart = x ………………(Particle filtering algorithm using matlab)

线性时不变离散时间系统在时域中可以通过常系数线性差分方程来描述，冲击响应序列可以刻画其时域特性。本实验通过使用MATLAB函数研究离散时间系统的时域特性，以加深对离散时间系统的差分方程、冲激响应和系统的线性和时不变特性的理解。(The linear time-invariant discrete-time system can be described in the time domain by a linear difference equation with constant coefficients. The impulse response sequence can describe its time-domain characteristics. This experiment uses MATLAB functions to study the time domain characteristics of discrete-time systems to deepen the understanding of differential equations, impulse response, and linear and time-invariant characteristics of the system.)

QR分解的MATLAB程序，可用于MIMO智能天线等(QR decomposition MIMO Smart antenna)

空时正交编码源程序，参考文献： V.Tarokh,H. Jafarkhani,and A. R. Calderbank "Space-Time Codes from ％Orthogonal Designs",IEEE Trans. Inform. Theory VOL. 45,NO. 5,JULY 1(orthogonal space-time coding source, References : V. Tarokh, H. Jafarkhani. and A. R. Calderbank, "Space-Time Codes from Or% thogonal Designs " IEEE Trans. Inform. Theory VOL. 45, NO. 5. JULY 1)

Guangxi M achinery No．2，2002 工程设计资料线图数据的MATLAB程序化(Guangxi M achinery No. 162-163 engineering design information and map data MATLAB program)

DC MOTOR CONTROL MATLAB

说明：  实现匹配滤波仿真的两个程序，每个程序生成四个图，可以通过比较验证信号的时延不影响匹配滤波的输出信噪比，及不同信号信噪比与信号波形无关，只与信号能量有关(Matched filter to achieve the two simulation procedures, each of the programs to generate the four plans, you can verify by comparing the signal delay does not affect the matched filter output signal to noise ratio, and different signal-noise ratio and signal wave has nothing to do only with the signal energy relevant)

MATLAB的课件集合，详细介绍了matlab的基础知识及其高级的应用，适合入门及进阶者。(MATLAB courseware collection, detailing the basics of matlab and its advanced applications, suitable for entry-and advanced persons.)

DIP text book kmeans image segmentation Input: ima: grey color image k: Number of classes Output: mu: vector of class means mask: clasification image mask