laogie

说明：  计算各种混沌系统李雅普洛夫指数的MATLAB 源程序。(calculating various chaotic system schematic index Lee MATLAB source.)

基于matlab的人工免疫遗传算法的编程（附注释）希望可以帮到大家 (Based on artificial immune genetic algorithm matlab programming (with comments) the desire to help people)

计算非线性系统的分叉图和李雅普诺夫指数，用于判断系统的混沌状态，独立的两个文件(a tool to calculate bifurcation and Lyapunov exponent)

说明：  利用GA遗传算法解决欺骗函数最优问题，具体问题描述如下，如有问题请与我联系(The deceptive functions are a family of functions in which there exists low-order building blocks that do not combine to form the higher-order building blocks. Here, a deceptive problem that consists of 25 copies of the order-4 fully deceptive function DF2 is constructed for this paper. DF2 can be described as follows: f(0000)=28 f(0001)=26 f(0010)=24 f(0011)=18 f(0100)=22 f(0101)=6 f(0110)=14 f(0111)=0 f(1000)=20 f(1001)=12 f(1010)=10 f(1011)=2 f(1100)=8 f(1101)=4 f(1110)=6 f(1111)=30 This problem has a maximal function value of 750.)

new robot search algorithms

以前用VB6编写的一个计算器，支持常用的数学函数，支持弧度、角度转换，支持简单的函数作图。(A calculator writen by VB6, supports common mathematical functions, support radian, angle conversion, support simple function mapping.)

梁的有限元开裂分析代码，包括不同的裂纹形式，裂纹数目等(Finite element analysis of beams cracking the code, including different forms of crack, crack number, etc.)

阻尼牛顿法、最速下降法、变尺度法的matlab程序。(Damped Newton' s method, steepest descent method, variable metric method matlab program.)

说明：  实现快速离散傅里叶变换，即FFT,很有用的程序(Fast discrete Fourier transform, namely, FFT, very useful program)

包括基本的克里金(Kriging)插值法实现代码，仅实现基本方法部分，不包含扩展克里金方法( kriging uses ordinary kriging to interpolate a variable z measured at locations with the coordinates x and y at unsampled locations xi, yi. The function requires the variable vstruct that contains all necessary information on the variogram. vstruct is the forth output argument of the function variogramfit. This is a rudimentary, but easy to use function to perform a simple kriging interpolation. I call it rudimentary since it always includes ALL observations to estimate values at unsampled locations. This may not be necessary when sample locations are not within the autocorrelation range but would require something like a k nearest neighbor search algorithm or something similar. Thus, the algorithms works best for relatively small numbers of observations (100-500). For larger numbers of observations I recommend the use of GSTAT. Note that kriging fails if there are two or more observa)