2.Correlation

说明：  用matlab编写了一个简单的元胞自动机交通可以进行多车道的模拟，有相关的函数(Prepared using matlab a simple cellular automaton can be multi-lane traffic simulation, have related functions)

bisection , Bi-section

地震资料处理的matlab程序，里面有好多好东西，有的改改就可以出文章的，可以合成测井记录及地震记录(seismic data )

基于s函数的spw仿真程序简单易懂便于操作(SPW simulation based on s function)

无约束优化,基于黄金分割的最速下降法极小化函数(Unconstrained optimization, based on the steepest descent method minimization function)

此为matlab教程，主要是关于simulink的实验教程，是学校的内部资料。(This is a matlab tutorial, mainly on the experimental simulink tutorial, is the school' s internal information.)

轨迹跟踪算法，能够有效降低噪声带来的影响(Trajectory Generation Using Sum-of-Norms Regularization)

线性预测分析是现代语音信号处理中最核心的技术之一，为现代语音信号处理的飞速发展立下了赫赫功劳，在语音分析、合成、编码、识别等方面都有着广泛的应用，至今仍是最有效的语音分析技术之一。(Linear prediction analysis is the most modern speech signal processing one of the core technology for the modern rapid development of voice signal processing and established illustrious contribution of the speech analysis, synthesis, coding, recognition and so on are widely used, still is the most effective voice analysis technologies.)

说明：  一个遗传算法的matlab程序，比较基础，也比较简单。(A genetic algorithm matlab procedures, basis of comparison, it is relatively simple.)

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.