final

The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically exact quadratic progress rate formula is derived. This is used to model the dynamical ES system by a set of difference equations. The solutions of this system are used to analytically calculate the optimal learning parameter  . The theoretical results are compared and validated by comparison with real (=I )-SA-ES runs on typical elliptic test model cases. The theoretical results clearly indicate that using a model-independent learning parameter  leads to suboptimal performance of the (=I )-SA-ES on objective functions with changing local condition numbers as often encountered in practical problems with complex fitness landscapes.

Image processing source code @ GIST

利用双谱分析信号的二阶非线性，检测信号的二次相位耦合(Spectral analysis of signals using two second-order nonlinear quadratic phase coupling detection signal)

说明：  一维波动方程的诺依曼计算，可以控制时间范围(Neumann calculation of one dimensional wave equation)

一种优化算法，在工业控制中应用很广，如用于PID参数整定等(this is an optimal algorithm,which is used in many aspects,such as PID tuning)

MAT lab source code need

计算神经网络学习过程中时间可塑性的依赖性的程序(compute time-dependant plastic)

说明：  遗传算法解决旅行商问题 main.m为主程序 可修改参数(Genetic algorithm for traveling salesman problem)

这是一个可以把四张图片合成一张图片的程序(This is a synthesis of four images can be a picture of the process)

说明：  最优化理论与方法课本算法matlab实现 二次插值法,包括抛物线插值和三点二次插值 具体使用方法详见程序说明(Optimization theory and methods of textbooks matlab algorithm to achieve quadratic interpolation, including the parabolic interpolation, and 3.2 times the specific use of interpolation methods detailed description of the procedures)