gcc

运用Matlab6.5实现跳频通信系统中跳频信号的时频分析(Matlab6.5 use of frequency hopping communication system to achieve frequency hopping signals in time-frequency analysis)

说明：  《模糊系统与模糊控制教程》共31章，内容包括模糊数学与模糊逻辑中一些对于模糊系统理论有用的概念和原理，模糊系统的各组成部分，设计模糊系统的四种方法，模糊控制与非自适应模糊控制方法，以及若干不属于本书主体结构但很重要的专题等内容。(Book a course of fuzzy systems and fuzzy control, a total of 31 chapters, including some of the fuzzy mathematics and fuzzy logic for useful concepts and principles of fuzzy system theory, fuzzy system of each component, design the four methods of fuzzy system, fuzzy control with the adaptive fuzzy control method, and some do not belong to book the main structure but very important project, etc.)

nmap最新windows环境下的源代码，对提高大家的编程能力有很大帮助(The latest source nmap windows environment, to improve our programming skills are very helpful)

模糊PID控制程序，采用MATLAB编写。(Fuzzy PID control procedures, the use of MATLAB to prepare.)

译码协同通信的蒙特卡洛仿真 基于最大比合并接收方法(Decoding the Monte Carlo simulation of cooperative communication)

this is a simulation of HVDC system

均匀线列阵，Capon波束形成，三方向入社，空间谱（功率谱）(Uniform linear array, Capon beamforming join a company in three directions, the spatial spectrum (power spectrum))

说明：  关于GA的c++代码和matlab代码的一个文件，可以做一个性能对比后，选择使用(On GA in c++ code and matlab code of a file, you can make a performance comparison, the option of using)

用PEG构造法生成LDPC监督矩阵的程序(With PEG construction method to generate LDPC matrix program oversight)

（1） 本系统用到四种神经网络对漏电嫌疑系数进行预测，分别是BP神经网络、RBF神经网络、GRNN神经网络、Elman神经网络，通过对神经网络结构参数的设置和调试，可以得到很好的预测效果，实际值和预测值之间的误差能达到5 以内。 （2） 本系统使用matlab做GUI界面，在界面上就可以分别对这四种神经网络的结构参数进行设置，从而可以调整神经网络的结构，达到较好的预测精度。 ((1) The system used four neural network to predict the suspected leakage coefficient, respectively, the BP neural network, RBF neural network, GRNN neural network, Elman neural network, the neural network structure parameter setting and commissioning, can get very good prediction, between the actual and predicted values ​ ​ of error of less than 5 . (2) the use matlab to do the GUI interface, the interface can each of these four neural network structure parameters set, the structure of the neural network, which can be adjusted to achieve better prediction accuracy.)