my-project

采用simulink对duffing和lorenz混沌系统进行仿真,然后又对lorenz混沌系统的进行延时反馈控制和同步控制,另外还有一个基于simulink的滑模控制,实现方便,效果不错!(Duffing using simulink for lorenz chaotic systems and simulation, and then lorenz chaotic systems on the conduct of delayed feedback control and synchronization control, there is another of the sliding mode control based on simulink to realize the convenience, good results!)

16QAM调制与解调的MATLAB实现及调制性能分析(MATLAB realization of 16QAM modulation and demodulation and modulation performance analysis)

实现ECG和BCG信号采集和同步监测，对采集的信号进行了特征量提取并作出相应诊断，波形显示在液晶屏上。(Achieve ECG and BCG signal acquisition and simultaneous monitoring of the collected signals feature extraction and make the appropriate diagnosis, the waveform displayed on the LCD screen.)

image resampling matlab coding(it is about resampling image)

gmsk modulation of numerical data generated by a random source, the output of the modulator give two signals, the first is gmsk signal and the other is gaussien frequency pulse shape

LDPC 64QAM 仿真的matlab源代码(Simulation of LDPC 64QAM)

说明：  偏最小二乘算法在MATLAB中的实现，直接将文件拷贝至matlab文件夹下，即可使用。详细使用方法见代码本身(Partial least-squares algorithm in MATLAB in the realization of a file copy directly to the matlab folder, you can use. See detailed use of the code itself)

this code plots the performance of BPSK modulation in various fading channels like rician, rayleigh and awgn channels.

The travelling salesman problem (TSP) or travelling salesperson problem asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city? It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.

说明：   开发环境:Matlab 简要说明:程序包含的设置包括：列数、样本总个数、建模样本数、预报因子数、预报对象数、学习因子、 动量因子、训练次数、总体误差、隐节点数。(development environment : Matlab brief description : program includes the installation including : number, the total sample number, the number of samples modeling, forecasting several factors, forecasting several targets, learning factor, momentum factor, the number of training, the overall error of hidden nodes.)