woundmotor

PSO与GA混合优化算法，可实现比单纯使用PSO或者GA算法更好的优化效果(PSO and GA hybrid optimization algorithm, can achieve more than a simple algorithm using PSO or GA optimization results better)

本本件主要使用MATLAB中的truetime工具箱仿真足球~(use the truetime box for soccer game~)

A pair of simple functions to make conversions between radians and degrees

本文件内容是聚类算法，对判别个体进行分类，十大经典算法之一，除了程序以外，还有详细的讲解，便于理解。(The contents of the documents clustering algorithm, determine the individual classification, one of the top ten classical algorithm, in addition to the program, there are detailed explanations, easy to understand.)

Channel equalization matlab sourcecode, fully functional with BER analysis

UN AUTRE MONDE DE LA VISION.............MATLAB..................SEGMENTATION

fuzzy control method for stability analysis of systems

PI控制的仿真模型模型，以及参数设置方面的相关问题。(PI control simulation model models, and parameter settings aspects related issues)

基于Matlab对约瑟夫森结（Josephson Junction）RCSJ模型的交直流I-V特性及非线性混沌现象进行数值模拟。通过计算机数值模拟得到该模型的非线性微分方程数值解，研究了RCSJ模型中各参量对约瑟夫森结的影响，进而简要分析其I-V特性和非线性混沌现象的产生机理，绘制出约瑟夫森结的交直流I-V特性曲线、非线性微分方程的相图及因其高度非线性而引起的通过倍周期分岔和阵发性原理进入混沌状态的分岔图。还给出庞加莱截面及功率谱。(Matlab based on the Josephson junction (Josephson Junction) RCSJ model AC and DC IV characteristics and non-linear numerical simulation of chaotic phenomena. Through computer simulation model by the numerical solution of nonlinear differential equations to study the RCSJ model parameters on the impact of Josephson junction, and a brief analysis of the IV characteristics and the emergence of the phenomenon of non-linear chaotic mechanism, drawn Josephson junction IV characteristic curve of AC-DC, non-linear differential equations and the phase diagram because of its highly nonlinear arising through period-doubling bifurcation and chaotic state of paroxysmal principle of access to the bifurcation diagram. Poincare cross-section and was also given power spectrum.)

Henon吸引子是混沌和分形的著名例子,迭代模型为xk+1=1+ax2k+byk,yk+1= xk.最常见的参数取值为a=1.4,b=0.3 .(The Henon attractor is chaotic and fractal famous example of the iterative model xk+1 = 1+ ax2k+ byk yk+1 = xk. The most common parameter values ​ ​ a = 1.4, b = 0.3)