svm

用基本粒子群算法来解决优化问题，本程序给出的是测试函数，根据需要可以自行更改适应度函数。(Using particle swarm optimization algorithm to solve the problem, this program is given a test function, you can change the fitness function according to their needs.)

模仿微信打飞机 的Demo 无bug 希望大家一起学习

#include <iostream.h> int main() { int i(0),sum(0) while (i<=100) { sum=sum+i ++i }cout<<"sum="<<sum<<endl return 0； }

说明：  VC与matlab的混合编写程序的COM方法，如何调用COM进行混合编程。(Mixture of VC and matlab programming of COM methods, how to call COM mixed programming.)

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说明：  一个用MATLAB实现的二阶系统的编程,想望对下载的人有用(this is a small file for two order styem by MATLAB ,I hope it will be useful to your.)

学习向量量化神经网络模型与学习算法及MATLAB实现(Learning vector quantization neural network model and learning algorithm)

搜集的一些matlab和vc++混合编程的资料，包含caj和pdf文档，很有实用意义！(collect some of Matlab and vc mixed programming information, contains PRODUCTS and pdf documents, It has practical significance!)

图1为均衡带限信号所引起失真的横向或格型自适应均衡器(其中横向FIR系统长M=11), 系统输入是取值为±1的随机序列，其均值为零；参考信号；信道具有脉冲响应： 式中用来控制信道的幅度失真(W = 2～4, 如取W = 2.9,3.1,3.3,3.5等)，且信道受到均值为零、方差(相当于信噪比为30dB)的高斯白噪声的干扰。试比较基于下列几种算法的自适应均衡器在不同信道失真、不同噪声干扰下的收敛情况(对应于每一种情况,在同一坐标下画出其学习曲线): 1）横向/格-梯型结构LMS算法 2）横向/格-梯型结构RLS算法 并分析其结果。(Figure 1 is a band-limited signal caused balanced horizontal or lattice distortion adaptive equalizer (FIR system in which the lateral length M = 11), the system input is the value of a random sequence of ± 1, mean zero reference signal channel has impulse response: Wherein the amplitude of the distortion for the control channel (W = 2 ~ 4, and so as to take W = 2.9,3.1,3.3,3.5), and subjected to a channel with zero mean and variance (equivalent SNR is 30dB) Gaussian white noise. Compare the following types of algorithm-based adaptive equalizer in a different channel distortion, the convergence of different noise interference (corresponding to each situation, draw their learning curve in the same coordinate): 1) landscape/grid- LMS algorithm ladder structure 2) landscape/grid- RLS algorithm ladder structure And analyze the results.)

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