brusslator

本程序实现汉字和字符的识别匹配，通过该算法，可以实现手写体的字符和汉字的识别(This procedure to achieve identification of characters and character matching, through the algorithm, can achieve the character and Chinese character handwriting recognition)

说明：  给定n种物品和一个背包,物品i的重量是Wi,价值是vi,被包容量是C,应该如何选择装入被包的物品,使得装入背包中物品的总价值最大?对于每种物品i,只有两种选择,装入或者不装入. 输入:第一行两个正整数n(物品数)和C(容量) 第二行n个正整数n,表示物品价值 第三行n个正整数n,表示物品重量 输出:第一行表示总价值 第二行n个数(0/1),0表示物品不装入,1表示装入 例如, 输入: 5 10 6 3 5 4 6 2 2 6 5 4 输出 15 1 1 0 0 1 (Species of a given n items and a backpack, the weight of item i is Wi, the value of vi, was packet capacity is C, should be how to choose a package of items to be loaded, the backpack load in the largest total value of goods? For each item i, there are only two options, loaded or not loaded. Input: the first line of the two positive integer n (the number of items) and C (capacity) of the second line of n positive integer n, that the value of the third line of n positive integer n, that the weight of output: the total value of the first line of the second line, said n number of (0/1), 0 that the items do not load, that load 1 for example, enter: 5,106,354,622 6 5 4 output 15 1 1 0 0 1)

说明：  用matlab仿真的递推极大似然法辨识程序，可用来进行系统辨识，很好用(simulation using Matlab Recursive maximum likelihood method identification procedures, which can be used for system identification, good use)

Goldestein unwrapping method

极限学习机分类与拟合,训练采用elmtrain.m，分类与拟合用elmprediction.m.(Extreme Learning Machine classification and fitting)

《有限单元法》一书中的相关程序，matlab变形，欢迎做有限元的人参考。("The finite element method," the relevant procedures, matlab deformation, welcome do finite element reference.)

HFSS_RF天线设计宝典。全彩页PDF。(hfss_rf anti design.all pdf)

rungekutta 2nd order pde

SRAD filetr for speckle reduction .This filter is a variant of anisotropic diffusion which successfully removes speckle type noise from images.

本文对变步长(VSS) 自适应滤波算法进行了分析,针对输入信号高度相关时算法收敛速度下降导致性能下降 的问题,提出了一种解相关变步长归一化LMS 自适应算法,引入相关性原理,使得算法保持良好的收敛性能。计算机仿真 结果与理论分析相一致(In this paper , we discuss and analyze the variable step2size adaptive algorithm(VSSLMS) ,in which the descent of it s convergence speed leads to the reduction of performance when input signals are heavily correlated . As a result , we propose an uncorrelated variable step2size normalized LMS adaptive algorithm. Due to the principle of correlation ,the algo2 rithm can achieve good performance. The simulations agree to the theoretical analysis.)