Learn-SVM-Step-by-Step-by-faruto2011

滑模变结构控制的一篇文章中的所有完整程序，包括庞加莱截面图，功率谱，相图，时域图，控制程序等等。(All the complete procedure of an article in the sliding mode variable structure control, including the Poincare map, power spectrum, phase diagram, time domain chart, control program etc..)

Magic number.. This programme can guess your decided number, by VB simple programme.

说明：  BP算法是为了解决多层前向神经网络的权系数优化而提出来的；所以，BP算法也通常暗示着神经网络的拓扑结构是一种无反馈的多层前向网络(BP algorithm is to solve the multi-layer feedforward neural network weights optimization and put forward Therefore, BP algorithm usually implies that the topology of neural network is a multi-layer feedback-free network)

MATLAB数字图像处理（张德丰）_书上源代码(MATLAB image processing (Zhang Defeng) _ source book)

matlab关于作图的讲解（有例题）包括二维，三维等等(explanations on the mapping matlab (with examples), including two-dimensional, three-dimensional, and so)

利用k-means方法对图像进行分类（matlab程序和c++程序），如对遥感图像分辨出河流、树木等，需要自己定义所处理图片位置，还有将分类的图片进行彩色区分(The use of k-means method for image classification (matlab program and c++ program), such as remote sensing images to distinguish rivers, trees, etc., need to define the position of the processed images, as well as the classification of images in color to distinguis)

IEEE 802.16d路径损耗模型属于对数正态阴影路径损耗模型。根据郊区宏蜂窝中发射机和接收机之间的障碍物密度，可以分为三种类型ABC。该代码利用MATLAB仿真了IEEE 802.16d路径损耗模型，并画出了未修正和修正的模型曲线以供对比参考。(IEEE 802.16d path loss models are lognormal shadow path loss model. According density suburban macrocell obstacle between transmitter and receiver can be divided into three types A B C. The code using MATLAB simulation of the IEEE 802.16d path loss model, and draw the uncorrected and corrected model curve for comparative reference.)

说明：  图4.7给出了V=4，相位集合的相位数分别为P=1、2、4、8时的随机分割的PTS-OFDM系统的CCDF的性能图。仿真参数：分割方法为随机分割，子载波数N=128，子载波数据采用QPSK调制，仿真的OFDM符号数为1000个。(Figure 4.7 shows the V = 4, the phase of the collection phase, respectively P = 1,2,4,8 were separated when the PTS-OFDM system performance CCDF graph. Simulation parameters: Segmentation of random division, the number of subcarriers N = 128, sub-carrier data using QPSK modulation, simulation of the OFDM symbol number 1000.)

布拉格光栅通过反射谱滤波仿真，使用矩阵算法(Bragg grating reflection spectra filtered through simulation, using the matrix algorithm)

盲源分离（BSS: Blind Source Separation），又称为盲信号分离，是指在信号的理论模型和源信号无法精确获知的情况下，如何从混迭信号（观测信号）中分离出各源信号的过程。盲源分离和盲辨识是盲信号处理的两大类型。盲源分离的目的是求得源信号的最佳估计，盲辨识的目的是求得传输通道混合矩阵。(Blind signal separation (BSS), also known as blind source separation, is the separation of a set of source signals from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process. This problem is in general highly underdetermined, but useful solutions can be derived under a surprising variety of conditions. Much of the early literature in this field focuses on the separation of temporal signals such as audio. However, blind signal separation is now routinely performed on multidimensional data, such as images and tensors, which may involve no time dimension whatsoever.)