HAS-App-Creation-Tutorial[V1.05]

灰色理论认为系统的行为现象尽管是朦胧的，数据是复杂的，但它毕竟是有序的，是有整体功能的。灰数的生成，就是从杂乱中寻找出规律。同时，灰色理论建立的是生成数据模型，不是原始数据模型，因此，灰色预测的数据是通过生成数据的gm(1,1)模型所得到的预测值的逆处理结果。(Gray theory that the behavior of the system even though the phenomenon is dim, the data is complex, but still it is ordered, there is a whole function. Gray number generation, that is, from the clutter to find out the laws. Meanwhile, the gray theory is to generate the data model, not the original data model, so gray prediction data by generating data gm (1,1) model predicted values ​ ​ obtained result of the inverse process.)

极值学习机的配套教程，上传给大家多学习学习吧。(Extremal supporting learning machine tutorial, upload to everyone to learn from it.)

了解隐马尔科夫模型HMM的概念、组成和需要解决的问题；通过matlab分析和三个基本算法分析读研和就业问题：forward算法、Viterbi算法和Baum-Welch算法(Understand the concept of Hidden Markov Model HMM, composition and problems to be solved matlab analysis by three basic algorithms: forward algorithm, Viterbi algorithm and Baum-Welch algorithm)

matlab实现包络检波的一个小函数，以及2FSK信号生成和相干解调(A small function to achieve Envelope detection)

该程序是RS编译码器的MATLAB仿真程序，里面有对程序的详细说明和解释。包括编码算法和译法算法的原理，流程以及代码实现。对掌握RS码有非常好的学习价值。()

Mobile User Localization

维也纳大学，LTE-A下行链路matlab链路级仿真程序。(University of Vienna, LTE-A downlink link level simulation matlab program.)

It is amplitude shift keying

基于扩展记忆的粒子群优化算法（Particle Swarm Optimization based on memory）(This paper combines SVM with improved PSO (Particle Swarm Optimization with Extended Memory, PSOEM) and then builds PSOEM-SVM forecasting model. The PSOEM searches the solution space intelligently and finds out the best one. Parameters in SVM are optimized by PSOEM, which implements automation of the parameter optimization avoiding the blindness of selecting parameters. Not only does it utilize the generalization feature of SVM, but enhance the global search ability of PSO (Particle Swarm Optimization). Thus, both accuracy and speed are increased at the same time.)

模拟透镜真实光路,厚的凸透镜，无小角度近似，使用真实光路追踪(Analog lens true optical path, the thickness of the lenticular lens, no small angle approximation, using the true optical path trace)