newton

这个程序可以修复因噪声/噪音干扰或者因抖动产生的失真的图像，Inverse滤波器, Wiener滤波器和Lucy-Richardson滤波器被使用到，同时代码还使用了光学流线分析，估计模糊的长度和角度。(This program can recover from noise/noise or distortion due to jitter generated images, Inverse filter, Wiener filter and the Lucy-Richardson filter were used, while the code also uses optical flow line analysis, estimated the length and fuzzy angle.)

基于ica的特征提取算法,主要是提取方向角特征.研究ICA的下载.(based on the genotype and phenotype of ica feature extraction algorithm, is the main feature extraction direction angle. Research ICA download.)

多输入多输出自适应，用于参数估计，有图。(matlab adaptive program for Parameter estimation)

VC与matlab混合编程方面的书籍，介绍全面，适用，是一本不错的书（英文）(VC and matlab mixing programming books, introduced comprehensively, applicable, is a good book (English))

eof分析的matlab软件包,需要输入的是距平序列，直接调用rest.m文件(a package of matlab codes on EOF analysis，the rest.m file is the main program )

原对偶内点法求解非线性最优化问题的测试程序，能准确快速的收敛到最优值(Primal dual interior point method for solving nonlinear optimization problem of the test procedure can accurately and quickly converge to the optimal value)

一份FDAtool使用、参数设置较详细的资料( FDATOOL)

Optimization of ackley function by Cuckoo with kmeansToolBox in matlab_coasite.info This code minimizes your cost function, so don t change any part of your code. -------------------------------------------------------------------------------------------------------------------------------------------------------------- *** ​ Cuckoo Optimization Algorithm *** Matlab Toolbox Ver. 1.0.1 *** Ramin Rajabioun, 2011 |

克里金法广泛地应用于地下水模拟、土壤制图等领域，是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布．确定对一个待插点值有影响的距离范围，然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后，为达到线性、无偏和最小估计方差的估计，而对每一个样品赋与一定的系数，最后　进行加权平均来估计块段品位的方法。(Kriging is a technique that provides the Best Linear Unbiased Estimator of the unknown fields (Journel and Huijbregts, 1978 Kitanidis, 1997). It is a local estimator that can provide the interpolation and extrapolation of the originally sparsely sampled data that are assumed to be reasonably characterized by the Intrinsic Statistical Model (ISM). An ISM does not require the quantity of interest to be stationary, i.e. its mean and standard deviation are independent of position, but rather that its covariance function depends on the separation of two data points)

formation control of cooperative robotic agents