基于遗传算法，进而优化惩罚因子-test_data

可用传输容计算程序，采用直流潮流计算，速度快。(Available transmission capacity calculation procedures, the use of DC power flow calculation speed.)

本文将迭代控制策略应用于双杆机器人，对于机器人的位置控制可实现无差跟踪。(This article iterative robot control policy to a double-pole, no difference tracking for the robot position control can be achieved)

Tests for <code>KeyPairGenerator</code> class constructors and methods.

It is about state vector machine.

改进小生境遗传算法求解多峰函数优化问题小论文主程序子程序（注释比较详细）(Improved Niche Genetic Algorithm for Multimodal Function Optimization paper)

详细介绍了matlab插值与拟合方法，包括拉格朗日多项式插值、牛顿插值、分段线性插 值、Hermite 插值和三次样条插值和曲线的最小二乘拟合、多项式拟合方法、最小二乘优化所有程序均有相应的说明与应用实例(Details of the matlab interpolation and fitting methods, including Lagrange polynomial interpolation, Newton interpolation, piecewise linear interpolation Value, Hermite interpolation and cubic spline interpolation and least-squares curve fitting, polynomial fitting method, least squares optimization program has all the appropriate instructions and application examples)

SVM的多类分类算法，可用于多类分类，里面有详细的例子(multi-class classification by SVM)

自己编写的QPSK调制与解调，内含matlab-figure-file、matlab-M-file和得出的jpg格式图形！(I have written QPSK modulation and demodulation, containing matlab-figure-file, matlab-M-file and come to the jpg format graphics!)

This script will setup the nonlinear simulation (UAV_NL.mdl) and call trim and linearization routines. Select the desired aircraft here in this script, via the "UAV_config()" function call.

粒子群算法(pso)标准测试函数验证程序。在一个m文件中包括了目前文献中用于验证的7个标准测试函数(Ackley等)、三维动态显示，粒子过分集中时打散等功能。旨在为学习和研究者pso算法的同仁提供一个功能较为完备、简单易懂的标准版本，对于初学者可以通过此程序快速的实现入门，以便将更多的精力投入到深层次的研究中去！同时愿与所有致力于此的朋友共同探讨pso算法的改进与应用方面(如多目标、动态系统等)的经验。(验。-PSO algorithm (PSO) standard test function verification process. M in a document, including the current literature is used to validate the seven standard test function (Ackley), 3D dynamic display, and the over-concentration of particles scatters when the function. Designed for researchers to study and colleagues at the PSO algorithm to provide a more complete functional and easily understood standard version, for beginners through this program to achieve rapid entry. in order to be more energy into depth study! While willing to work with all the friends here to discuss PSO algorithm improvements and applications (such as multi-target, Dynamic systems, etc.) experience.)