Matlab2001B

demo Learning-Vector-Quantization

时频分析书籍，语言比较通俗易懂，写的不错(Time-frequency analysis theory and application)

It is an ebook about the mathematical portion of teh GRE preparation class. it have all the problems related to different chapters and practise questions

在一个移动通信系统中，发射信号是一个未调制的音频x(t)=cos(2πft)，其中f=f0+fi。设标称载波为f0=1GHz，并设fi =512Hz。假定移动用户在一个繁忙的高速公路上距离基站l公里处的地方，从开始从每小时60公里的速度开始，其速度（在0.01秒的时间间隔内测量）以1/2的概率随机的增加或减少1/10公里每小时。试仿真移动用户在这2s的时间间隔内所接收到的信号(及其频谱)。接收信号可以表示为： y(t)=a(t)Cos[2π(fo+f1)(t-△t)] 式中 △(t)=d(t)/c 且 a(t)=k/d2(t) 在上面的表达式中d(t)是在t时刻基站与移动用户的距离，c是光速，△(t)是传播延迟，而a(t)是信号在t时刻的衰减，并假设在这2s内a(t)是一个常数。利用复低通等效模型来进行仿真。(In a mobile communication system, the transmitted signal is an unmodulated audio x (t) = cos (2πft), where f = f0+ fi. Let nominal carrier of f0 = 1GHz, and set fi = 512Hz. Assume that mobile users on a busy motorway station l kilometers place, starting the beginning of 60 kilometers per hour, the speed (measured in 0.01 second interval) to increase the probability of a random 1/2 or reducing 1/10 km/h. Simulation test signal which the mobile subscriber in the 2s time intervals of the received (and its spectrum). The received signal can be expressed as: y (t) = a (t) Cos [2π (fo+ f1) (t- △ t)] Where △ (t) = d (t)/c And a (t) = k/d2 (t) In the above expression, d (t) at time t is a base station and a mobile user s distance, c is the speed of light, △ (t) is the propagation delay, and a (t) is the attenuation of the signal at time t, and assuming that 2s within a (t) is a constant. Using complex low-pass equivalent model for emulation.)

UKF无迹卡尔曼滤波用于地磁场的计算，但由于保密原因，录入的数据信息已删除，主要用于UKF框架的交流(Unscented Kalman filter UKF is used to calculate the magnetic field, but because of confidentiality reasons, the entry of data has been deleted, the main framework for the exchange of UKF)

see guys here is the code refer and take it

code based on cardiovascular images for extracting intima media layer

A Vector Quantization Technique for Image Compression using Modified Fuzzy Possibilistic C-Means with Weighted Mahalanobis Distance

说明：  在基于事件的情况下将分数阶PI-PD控制器离散实(The fractional order PI-PD controller is discretized based on event)

maltab优化工具箱的一些小例子 主要介绍最优化的相关知识 欢迎大家共同探讨(optimization toolbox maltab some small examples are introduced to optimize the relevance of knowledge welcome you to explore)