matlab-uimenu

image processing and key generation etc

说明：  图像混沌加密matlab仿真程序，用MATLAB编程实现的将混沌应用于图像加密的算法.(Chaotic encryption image matlab simulation program, using MATLAB programming will be chaotic image encryption algorithm used.)

一维配点型无网格算法matlab程序，以一维单位长度杆为例子。(ONE DIMENSIONAL Collocation-based MESHLESS PROGRAM FOR SOLVING A 1D BAR OF UNIT LENGTH SUBJECTED TO A LINEAR BODY FORCE OF MAGNITUDE X WHOSE EXACT SOLUTION IS GIVEN BY u = (x/2- x^3/6)/E)

the matlab code for support vector regression machine , including data pretreatment of information. It includes an example (time prediction series)that uses SVR

用DCT方法嵌入一个水印图片，并生成R层图片(DCT method to use a watermark embedded images, and generate R layer picture)

半正定矩阵cholesky方法将其分解为两个上下三角矩阵相乘的形式。matlab自带的函数只能分解正定矩阵。并且给出例子。(Semi-definite matrix cholesky method be decomposed into two upper and lower triangular matrices form. matlab built-in function can only be positive definite matrix decomposition.)

复杂网络matlab样例（只要为sy003.m），包括求平均度，路径直径，平均路径长度，聚类系数，介数（需要加载bgl工具箱），核数，紧密度等(Complex network matlab sample (as long as it sy003.m), including the degree of averaging, the path diameter, the average path length, clustering coefficient, betweenness (bgl need to load the toolbox), auditing, tightness, etc.)

对一种三相无源功率因数校正电路进行了参数的优化和仿真，仿真结果表明，运用Matlab中的SimPowerSystems模块对复杂的电路进行仿真分析和研究，不失为一种准确、直观有效的方法。 (Of a three-phase passive power factor correction circuit parameter optimization and simulation results show that the use of Matlab in SimPowerSystems module circuit simulation of complex analysis and research, after all, a precise, direct and effective way.)

MATLAB 通信仿真的基本调制程序，M源文件格式。(matlab basic modulation(BPSK,QPSK,QAM,GMSK......))

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.