Radial-neural-network

地震瞬时属性提取时，HIlbert变换很重要，本程序基于MatlAB，处理了单道地震信号，可供地震资料处理的初学者学习(When seismic instantaneous attributes, HIlbert transformation is important, this program is based on MatlAB, the single-channel seismic signal processing, seismic data processing for beginners)

Gauss_generator利用参数（多普勒频移、系数、相移）生成确定的实高斯过程.m gaussian确定离散多普勒频移、系数、相移的程序.m Rice_generator在瑞利过程的基础上考虑视距分量，生成莱斯过程.m Suzuki_generator成确定型Suzuki过程.m Rayleigh_Doppler_multiPath.m Rayleigh_Doppler_singlePath.m rayleigh_Filter_Model.m pdf_cdf_gen.m test_rayleigh_pdf.m rayleigh.m(Gauss_generator use parameters (Doppler frequency shift coefficient, phase shift) formation to determine the actual Gaussian process. m Gaussian identify discrete Doppler frequency shift coefficient, Phase-shifting procedures. m Rice_generator in Rayleigh process on the basis of weight to consider the horizon, Rice production process. m-Suzuki_generator identified as Suzuki process. m Ra yleigh_Doppler_multiPath.m Rayleigh_Doppl er_singlePath.m rayleigh_Filter_Model.m pd f_cdf_gen.m test_rayleigh_pdf.m rayleigh.m)

说明：  matlab 复杂网络小世界网络模型原matlab程序(Matlab complex network small world network model of the original matlab program)

per-task delay accounting.

说明：  干涉相位滤波（均值、中值、圆周期）用于insar的三种不同滤波方法(Three different filtering methods for InSAR based on interferometric phase filtering (mean, median and circle period))

studying the performance of the electronic AC voltage regulator using matlab

计算魔方矩阵 是纯属于 手工打入 有意思 值得看(Cube matrix is calculated purely by hand into interesting to see in)

The package includes the source code of the library in C++ and Java, and a simple program for scaling training data.

说明：  基于matlab的图像配准程序，算法使用的是sift原理，配准效果良好(Matlab based image registration procedures, the algorithm uses the principle of SIFT, registration good results)

说明：  径向基函数神经网络的优点：逼近能力，分类能力和学习速度等方面都优于BP神经网络，结构简单、训练简洁、学习收敛速度快、能够逼近任意非线性函数，克服局部极小值问题。原因在于其参数初始化具有一定的方法，并非随机初始化。代码为RBF的matlab程序，可以使用但是需要自己配置数据。(Radial Basis Function Neural Network (RBF-NN) has the advantages of better approximation ability, classification ability and learning speed than BP Neural Network (BP Neural Network). It has simple structure, simple training, fast learning convergence, and can approximate any non-linear function to overcome the local minimum problem. The reason is that its parameter initialization has a certain method, not random initialization.)