colorspace

数值分析中基于Matlab环境下的关于最小二乘的源代码(Numerical analysis environment based on Matlab source code on least-squares)

Volterra级数模型对功放建模仿真,Matlab编程代码(On the series model for power amplifier modeling simulation, Matlab programming code )

无功补偿器statcom的仿真图，运行良好，可以改进欢迎提意见很分享(Var Compensator statcom simulation map, running well, you can improve it are welcome to share comments)

matlab中解调谱的示例程序，操作简单，可直接复制，便于调用。(spectrum demodulation in matlab sample program, simple operation, can be directly copied, easy call.)

matlab小波分析和图像检测的内容，运用matlab实现上述算法和运用(Matlab wavelet analysis and test, the contents of the image using matlab the above algorithms and use)

说明：  直流微电网故障仿真模型，还不错，控制模块可以参考下。并网方式可学习。(The fault simulation model of the DC microgrid is not bad, and the control module can be referred to. You can learn how to connect to the network.)

设计2.4GHz的短距离无线传输天线的资料(The data for designing 2.4GHz SRD wirless antenna)

灰色预测模型,可以做变形监测预测分析，交通控制和预测分析，金融分析(Gray prediction model, deformation monitoring can do predictive analysis, traffic control, and predictive analysis, financial analysis)

经典的多核学习工具箱，功能强大，内容全面(The classic multi-core learning toolbox, powerful, comprehensive)

An important aspect of an ANN model is whether it needs guidance in learning or not. Based on the way they learn, all artificial neural networks can be divided into two learning categories - supervised and unsupervised. • In supervised learning, a desired output result for each input vector is required when the network is trained. An ANN of the supervised learning type, such as the multi-layer perceptron, uses the target result to guide the formation of the neural parameters. It is thus possible to make the neural network learn the behavior of the process under study. • In unsupervised learning, the training of the network is entirely data-driven and no target results for the input data vectors are provided. An ANN of the unsupervised learning type, such as the self-organizing map, can be used for clustering the input data and find features inherent to the problem.