nn_rbf_learning

说明：  双馈电机数学模型，基于simulink，如果需要可以提供S函数的模型(Doubly-fed machine mathematical model, based on simulink, if necessary can provide a model S function)

robust filtering in Krein space

干扰信号估计仿真程序程序，matlab仿真程序(Interference signal estimation procedure simulation program, matlab simulation program)

TE波在二维自由空间的传播 Mur边界 高斯源(TE wave propagation in two-dimensional free-space Gaussian source Mur boundary)

说明：  matlab灰色关联算法，新手入门例程，附代码脚本(Matlab grey association algorithm novice routine, with code script.)

物理层的空时编码的MATLAB仿真程序，包含发射端、信道到接收端的所有源代码(space-time coding project)

最小均方濾波器是一類可通過最小化誤差訊號之均方值而修正濾波器係數，以類比所需理想濾波器的自適應濾波器，其中作為修正依據的誤差訊號為理想參考訊號與實際輸出訊號之差。該種濾波器所用之最小均方法只以當前之訊號誤差值為準進行修正，是一種隨機梯度下降法。最小均方法係由斯坦福大學的Bernard Widrow教授及他的首位博士班學生Marcian Hoff於1960年提出。最小均方濾波器屬於常見的自適應濾波器種類之一。(The minimum mean square filter is an adaptive filter that can correct the filter coefficients by minimizing the mean square value of the error signal to analogize the desired ideal filter. The error signal used as the correction reference is the ideal reference signal and the actual output. The difference between the signals. The minimum averaging method used in this kind of filter is only corrected based on the current signal error value, which is a stochastic gradient descent method. The minimum mean method was proposed in 1960 by Professor Bernard Widrow of Stanford University and his first PhD student, Marcian Hoff. The least mean square filter is one of the common types of adaptive filters.)

基于Simulink的小车_倒摆模糊自适应控制系统设计与仿真(Simulink based on the car _ inverted pendulum fuzzy adaptive control system design and simulation)

对数据中出现的情况分为三类进行匹配，正常，不正常，和未知，对不正常的数据进一步分析- (data on the case are divided into three types matching, normal, abnormal, and unknown, not normal for further analysis of the data-)

The following Matlab project contains the source code and Matlab examples used for use fourier interpolation to increase sampling of an image. also includes an optional filter. . Zero-pads the FFT of an image up to the desired size, then performs IFFT on larger array.