PSO

Solving Engineering Problems Using MATLAB C++ Math Library Introduction In the previous article, we studied how can use MATLAB C API to solve engineering problems. In this article I will show you how can use MATLAB C++ math library. The MATLAB® C++ Math Library serves two separate constituencies: MATLAB programmers seeking more speed or complete independence from interpreted MATLAB, and C++ programmers who need a fast, easy-to-use matrix math library. To each, it offers distinct advantages.

a generic particle swarm optimizer

在工程应用中 经常会遇到一些复杂的非线性系统, 这些系统状态方程复杂, 难以 用数学方 法准确建模。 在这种情况下, 可以 建立 BP 神 经网 络表达这些 非 线 性系 统。 该方法把未 知 系 统看成是一个黑箱, 首先用 系 统 输入输出 数据 训 练 BP 神 经网 络, 使网 络能 够表达该未 知 函 数, 然后就可以 用训练好的 BP 神经网络预测系统输出 。 本章拟合的非线性函 数为 y = x1^2+x2^2. 。 (In engineering applications often encounter some complex nonlinear systems, which complicated the equation of state, can not be accurately modeled mathematically. In this case, BP neural network can be established to express these nonlinear systems. The method of the unknown system as a black box, the first input and output data with systematic training BP neural network, the network can express the unknown function, then you can use the trained BP neural network forecasting system output. Chapter for fitting non-linear function y = x1 ^ 2+x2 ^ 2..)

这个程序就是最基本的粒子群优化算法程序，用Matlab实现，非常简单。(This program is the most basic particle swarm optimization algorithm and Matlab, very simple.)

三维直角坐标系FDTD应用UPML吸收边界条件，激励源为高斯脉冲(Three-dimensional Cartesian coordinate system FDTD application UPML absorbing boundary conditions, excitation source for the Gaussian pulse)

说明：  EEGLAB学习资料，对出学习和有很大的帮助，希望对你有用(EEGLAB learning materials, on the study and a great help, I hope useful to you)

QEA for knapsack problem

说明：  matlab的qpsk的程序代码 是初学者的福音(The qpsk matlab program code is the gospel for beginners)

matlab 入门教程 适合刚入门的学生学习(matlab Tutorial)

偏微分方程的MATLAB解法 对学习matlab环境下计算偏微分方程有很好的帮助。同时，也可以用其中的PDEOOL为计算流体力学中的二维问题生成三角形网格，减少前处理工作量(Solution of Partial Differential Equations MATLAB computing environment for learning matlab partial differential equations have a good help. Also, you can use one of the PDEOOL for the two-dimensional computational fluid dynamics problems in the triangular mesh generated, reduce the workload of pre-treatment)