research_synchronization_in_DSSS

模糊免疫 PID 控制算法,在模糊控制的基础上，增加了免疫因子，能获得更好的控制效果(Fuzzy immune PID control algorithm, in the basis of fuzzy control, an increase of immune factors that can effect a better control)

这是一个通信系统的仿真，是用SIMULINK的S-FUNCTION方式编写的，共有20个M文件，1个DOC文件，本系统的仿真设计到编码、调制、IFFT、上下变频、高斯信道建模、FFT、PAPR抑制、各种同步、解调和解码等模块，每个模块都用详细的代码和注释，并通过了系统性能的仿真验证了系统设计的可靠性，可以直接拿来仿真整个系统，也可来学习各个部分的设计。(This is a communication system simulation, is the S-FUNCTION SIMULINK approach to the preparation, a total of 20 M file, a DOC file, the system simulation design to coding, modulation, IFFT, and down conversion, Gaussian channel model , FFT, PAPR suppression, various synchronization, demodulation and decoding modules, each module with a detailed code and comments, and system performance through simulation and verification of the reliability of system design, simulation of the entire system can be directly used, also to learn the various parts of the design. )

压缩文件中是Maple程序设计.doc，总结了一些简单的maple软件的用法(Compressed file is Maple programming. Doc, summarizes some simple maple software usage)

Scientific and Engineering C++. Book for developing applications in C++

图像模板匹配算法用MATLAB来试验，有例子大家可以看看，有上占还不完好，有能力的自己改改(Image template matching algorithm using MATLAB to test, there are examples we can see, there are not well accounted for, the ability of their changed)

图像之后可以用来计算二维图像的形心坐标与二维图像目标物的面积。有实例图片。(After the image is two-dimensional image can be used to calculate the coordinates of the centroid of the area of ​ ​ the two-dimensional image of the target object. There are examples of pictures.)

可进行图像分割 对于光纤图像 可分别初芯婧与外套(Image segmentation can be performed separately for the beginning of the image fiber core and the jacket Jing)

task graph generator: task graph for free version 3.5

说明：  本实验的目的是了解非参数估计--parzen窗估计，对数据进行Parzen窗估计和设计分类器。并分析窗口宽度h对分类的影响。(The purpose of this study is to understand the non-parametric estimation- parzen window estimation, Parzen window estimate of the data and design of classifiers. Window width h and analyzed the impact on the classification.)

this is simple implementation of forecasting using neural network backpropagation