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ADVANTAGES OF DETECTION TECHNIQUE

基于遗传算法的多目标函数优化问题的一种有效方法(An effective method for multi-objective optimization problem based on genetic algorithm function)

resolution de l equation NLSE avec l efet de Raman

Differential Evolution

这是一个简单的FFT为无电位1 +1 +1 Ð 薛定谔方程的光束传播方法。如果该软件灵活，允许引入的术语（如果是极少数需要包括色散效应高阶导数）。例如，如果一个人渴望解决的一个方程的形式： （四/ dz的+ Ð ^ 2/dx ^ 2 - 0.25 * Ð ^ 3/dx ^ 3）== 0 Ÿ 它可以解决使用以下代码： Ž = linspace（0,1,512） x = linspace（-5,5,1024） psi0 =进出口（- x的。^ 2） Ð = D_lateral1D（十，2）-0.25 * D_lateral1D（十，3） 字段= LinearBPM（psi0，有D，Z） 凡D_lateral1D是一个函数，提供“取代”的微分算子。 这个函数是在一个非线性的BPM，我曾对（分步，谱方法等），将提交给我，当我完成他们的文件和组织功能更复杂的设置非常初期阶段。 (This is a simple FFT based beam propagation method for potential-free 1+1+1D Schrodinger equation. The software if flexible and allows to introduce high-order derivatives in the term (very handful if is needed to include dispersion effects). For example, if one desires to solve an equation in the form: (d/dz+ d^2/dx^2- 0.25*d^3/dx^3)Y == 0 It can be solved using the following code: z=linspace(0,1,512) x=linspace(-5,5,1024) psi0=exp(-x.^2) D=D_lateral1D(x,2)-0.25*D_lateral1D(x,3) field=LinearBPM(psi0,D,z) Where D_lateral1D is a provided function that "replaces" the derivative operator. This function is a very early stage in a more complex set of non-linear BPM functions that I have made (split-step, spectral methods, etc.) and I will submit them when I finish their documentation and organization. Sorry for my English, I m eager for your comments. )

粒子群算法 很实在的程序敬请大家下载。保证不会后悔(PSO program is really please you to download. Guaranteed not to regret)

说明：  利用自然梯度算法，仿真盲信号分离过程，并给出学习收敛曲线(Use of natural gradient algorithm, simulation blind signal separation process, and gives the convergence curve of learning)

The third element has been removed the list. The list has now only four elements. It is not possible to delete more than one element at a time in this way

关于时钟同步timing synchronization 的例程，参数可重设，有注释(timing_syn.m timing synchronization )

说明：  用L-M 优化算法与贝叶斯正则化算法训练同一个样本(By LM optimization algorithm with Bayesian regularization algorithm for training with a sample)