NEDI

该文件内含有程序和详细的程序解读，从不同的角度完成统一任务：卷积编码(The document contains the procedures and detailed procedures for reading from a different point of view the fulfillment of the tasks: convolutional coding)

说明：  本算法介绍了朴素贝叶斯算法的原理和功能以及使用MATLAB实现其功能算法。(This algorithm describes the principle of Bayesian algorithms and functions and the use of MATLAB algorithms to achieve its function.)

关于MATLAB图形用户界面(GUI)初学者指导教程系列，有较详细的说明和指导(On the MATLAB graphical user interface (GUI) Beginners Guide series, has a more detailed explanation and guidance)

Softmax 函数处理，softmax 用于 Deep Learning 后的分类器的实现与识别，此函数的参数经过优化，有较强的泛化能力和性能(Softmax function processing, softmax classifier Deep Learning for the realization and recognition, the parameters of this function is optimized, there is a strong generalization ability and performance)

仿真2×1瑞利信道，分别考虑三种接收分集技术：最大比合并、等增益合并、选择性合并，并给出误码率比较。(In a one transmitting antenna and two receiving antenna collocate,calculate the bits error rates of the maximum ratio combining,equal gain combining ,selective combining and SISO system)

通过matlab实现拉格朗日乘子法。学习经典优化方法，熟悉matlab语言。(Realize the Lagrangian multiplier method by matlab. Learning classic optimization methods, familiar with matlab language.)

连续隐马尔可夫识别程序。 包含的模块，可以比较完整地进行语言识别。 主要模块： Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m (speech recognize using HMM include 11 matlab fuction: Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m )

该程序实现了压缩感知理论中采用矩阵的优化。在压缩感知理论中，要求采样矩阵与稀疏矩阵的相关性越低越好。该代码采用一种交替投影的方法实现采用矩阵的优化，有效降低其相关性。(The program to achieve the optimization of the use of matrix theory compressed sensing. Requirements of the sample matrix and sparse matrix theory of compressed sensing, the lower the better. The code uses an alternating projection method to achieve the optimization of the use of matrix to effectively reduce the correlation.)

说明：  局部碰磨事故检测代码，通过功率谱检测，例子检测了四种类型的碰磨事故(Partial rubbing incident detection code, through the power spectrum detection, examples of detection of the four types of rub-impact accident)

很好用，用matlab编的偏最小二乘法，直接在matlab里就可以用。另外带有PLS讲解(Good use, with the partial least squares matlab compiled directly in matlab can be used inside. In addition to explain with PLS)