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基于模糊rbf网络的逼近算法及仿真实例源代码，包括学习算法等(rbf)

说明：  OFDM的仿真，这种技术wimax已经采用，未来的4G肯定也是基于这种技术。附件是源代码，仅供大家参考！ (OFDM simulation, WiMAX technology has been adopted as the future 4G is definitely based on the technology. The annex to the source code, only your reference!)

研究用于自适应均衡器的LMS算法。研究步长的影响。分别画出W=2.9时，mu= 0.01、0.04和0.08情况下的MSE学习曲线(Research for the adaptive LMS algorithm equalizer. Research on the impact of the step. Draw W = 2.9, respectively, when, mu = MSE learning curve 0.01,0.04 and 0.08 in case of)

EKF(扩展卡尔曼滤波)和UKF（无迹卡尔曼滤波）对比 RMSE曲线对比(Contrast curve comparison RMSE (unscented Kalman filter) EKF (extended Kalman filter) and UKF)

并联有源共模电流抑制方法的matlab仿真，建立仿真模型，分析补偿特性(common mode current inhibition of Matlab simulation, simulation model building, analyzing characteristics compensation)

implementation of segmentation and edge detection by metlan code is standard//

WIM2-ITU的Matlab 文档，很有借鉴性(WIM2-ITU Matlab documentation)

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.)

用函数归一化逼近一个正弦函数，学习采用采用自适应方法(Function normalized with a sine function approximation, learning the use of adaptive methods )

Voltage sag reduction in SIMULINK