FCMvsKMeans

2ASK(1)通信系统仿真进行2ASK调制，其中基带信号为单极性NRZ矩形波，采用相干解调方法对带通滤波器的输出信号进行解调；(2ASK (1) 2ASK modulation for communication systems simulation, in which the baseband signal is unipolar NRZ square wave, coherent demodulation method using band-pass filter output signal demodulation )

波束形成中mvdr和music算法精确性对比分析，可对两个声源进行识别(Mvdr and music beamforming algorithm accuracy comparative analysis of the two sound sources can be identified)

simulation of clamping unit of injection molding machine

Codigo para diferenciar el numero 6 con el 9

可以用于求解两个信号的互信息、信息熵，并在此基础上求解广义相关系数。(Mutual information, information entropy can be used to solve the two signals, and solving the generalized correlation coefficient on this basis.)

这个示范ilustrates使用的三相Programmble电压源，PLL和可变频率正序电压和功率的测量块(This demonstration ilustrates use of the 3-Phase Programmble Voltage Source, PLL and Variable-Frequency Positive-Sequence Voltage and Power Measurement blocks)

信号，噪声，信号加噪声，FFT，matlab仿真,时域波形，频谱图(Signal, noise, signal plus noise, FFT, Matlab simulation, time-domain waveform, spectrogram)

只是一个关于用共轭梯度下降算法处理数据的程序，本程序处理的数据对象为MINST,该程序在线性搜索上有很好的效果(Only one on the use of conjugate gradient descent algorithm data processing procedures, the procedures for processing the data object is MINST, linear search for the program have a good effect on)

说明：  ELM机器学习模型，基本参数需要进行适当调整(ELM machine learning model, basic parameters need to be adjusted appropriately)

The shuffled complex evolution with principal components analysis–University of California at Irvine (SP-UCI) method is a global optimization algorithm designed for high-dimensional and complex problems. It is based on the Shuffled Complex Evolution (SCE-UA) Method (by Dr. Qingyun Duan et al.), but solves a serious problem in searching over high-dimensional spaces," population degeneration". The population degeneration problem refers to the phenomenon that, when searching over the highdimensional parameter spaces, the population of the searching particles is very likely to collapse into a subspace of the parameter space, therefore losing the capability of exploring the entire parameter space. In addition, the SP-UCI method also combines the strength of shuffled complex, the Nelder-Mead simplex, and mutinormal resampling to achieve efficient and effective high-dimensional optimization.