FM

Once chosen the angle of incidence, does the graph of the transmittance as a function of frequency.

matlab建模，在数学建模竞赛中的应用(matlab modeling, mathematical modeling contest in the application)

此例程可以用来进行希尔伯特变换，得到包络谱，利用差分公式得到瞬时频率(This routine can be used to carry out Hilbert transform, obtain envelope spectrum, and obtain instantaneous frequency by using difference formula)

说明：  一种改进的DE算法，来自文献“JADE: Adaptive Differential Evolution with Optional External Archive”(JADE: Adaptive Differential Evolution with Optional External Archive)

这是"Matlab从入门到精通"一书的全部源代码程序！有兴趣的人员可以自己跑跑看看结果！(This is the " Matlab from the entry to the master," a book full source code program! Interested persons may look at the result that running their own!)

Source separation problems in digital signal processing are those which are used to separate useful signal a mix of signals of interest, other signals and noise. The typical example of a source separation problem is the cocktail party problem, where many number of peoples are talking simultaneously in a room and a listener is trying to follow one of the discussions. The human brain can separate the voices of different people (source separation) using neurons in the auditory region. But source separation using digital signals is difficult task with the available techniques. Several approaches have been proposed for solving this issue but most of the techniques are still in development stages. Some of the successfully tested approaches are principal components analysis (PCA) and Independent components analysis (ICA). Both the approaches work well when there are no delays or echoes present

应用四步相移法实现包裹相位的解缠，另有解缠结果(Application of four step phase shifting method to achieve the wrapped phase unwrapping, otherwise the unwrapping results)

FFT的MATLAB仿真实验，了解关于MATLAB的一般过程，及波普分析方法(FFT MATLAB simulation experiments to understand the general process of MATLAB, and pop analytical methods)

MATLAB处理神经网络的43个案例，推荐学习(MATLAB neural network processing 43 cases, it is recommended to learn)

说明：  NN neural network for face recognition supervised feed forward back propagation neural network