GSO

基于matlab的人工神经网络的实现,m语言 (matlab achieve ann)

RBF for classification in matlab with GUI

三电平仿真模型，相对两电平谐波更小，极有参考价值(Tri-level simulation model of two level harmonic smaller, relatively great reference value)

使用svm进行数据的预测，首先进行pca对数据进行主元分析，提取有用信息，结果显示数据拟合效果非常好(SVM is used to predict data. first, PCA is used to analyze the data and extract useful information. the results show that the data fitting effect is very good.)

说明：  基于MATLAB软件下的小波变换代码，实现小波变换对图片的压缩处理(MATLAB software based on wavelet transform under the code, the realization of wavelet transform for image compression)

一个标准PCA的学习实例，通过matlab可运行，希望对大家有所帮助(A standard PCA learning instance, through matlab to run, we want to help)

SVPWM转子磁链定向矢量控制 效果佳！(SVPWM FOC)

说明：  多目标粒子群算法，双目标函数，求解帕累托最优(Multi objective particle swarm optimization algorithm)

denoise In BayesShrink[5] we determine the threshold for each subband assuming a Generalized Gaussian Distribution(GGD) . The GGD is given by GG¾ X ¯ (x) = C(¾ X ¯ )exp¡ [® (¾ X ¯ )jxj]¯ (6) ¡ 1 < x < 1 ¯ > 0, where ® (¾ X ¯ ) = ¾ ¡ 1 X [ ¡ (3=¯ ) ¡ (1=¯ ) ]1=2 and C(¾ X ¯ ) = ¯ ¢ ® (¾ X ¯ ) 2¡ ( 1 ¯ ) and ¡ (t) = R1 0 e¡ uut¡ 1du. The parameter ¾ X is the standard deviation and ¯ is the shape parameter It has been observed[5] that with a shape parameter ¯ ranging from 0.5 to 1, we can describe the the distribution of coefficients in a subband for a large set of natural images.Assuming such a distribution for the wavelet coefficients, we empirically estimate ¯ and ¾ X for each subband and try to find the threshold T which minimizes the Bayesian Risk, i.e, the expected value of the mean square error.

Matlab 无标度网络 可以任意增加节点，边的数量(Matlab scale-free network nodes can be arbitrarily increased, the number of edges)