使用python实现搜索和广深（人工智能）

用sobel算子实现边缘检测源代码，用C++实现了sobel算子。图像编码完整实现。

数值分析中的迭代法解线性方程组问题，含输入输出界面。-Numerical analysis of iterative method for solution of problems of linear equations, including input and output interface.

This algorithm was developed by Professor Ronald L. Rivest of MIT and can be found presented in several languages. What I provide to you here is a C++ derivative of the original C implementation of Professor Rivets. The library code itself is platform-independant and has been tested in Redhat Linux. I ve included the sample code and makefile that I used for the Linux test. The demo, however, was written with Visual C++ 6 on a Windows 2000 platform.-This algorithm was developed by Professor Ronald L. Rivest of MIT and can be found presented in several languages. What I provide to you here is a C derivative of the original C implementation of Professor Rivets. The library code itself is platform-independant and has been tested in Redhat Linux. I ve included the sample code and makefile that I used for the Linux test. The demo, however, was written with Visual C 6 on a Windows 2,000 platform.

Huffman编码1． 给出信源符号的一阶概率分布，并计算信源符号熵和单字符Huffman码表。2． 计算每信源的平均字长，并与信源符号熵比较。3． 比较压缩效果。-Huffman coding 1. Source symbols are given first-order probability distribution, and calculate the entropy source and single-character symbols Huffman code table. 2. Calculated the average per source word length, and entropy source comparison symbols. 3. Comparison of the effect of compression.

c++ 语言实现算法，用的时候把数据集里面的数据放到C盘下，直接运行就行，数据集提供了两种，方便计算

PDKS是屈崑在新加坡国立大学攻读博士学位期间研究可压缩 LBM模型时开发的程序LBM可压缩流模拟程序。基本特点为： 请点击左侧文件开始预览 ！预览只提供20%的代码片段，完整代码需下载后查看 加载中 侵权举报

一般的快速DCT算法只有8点和16点的，我这里提供任意长度（2的幂次方）的DCT快速算法原代码-general fast DCT algorithm only 8:00 and 16:00, and here I am of arbitrary length (two of the power law) DCT fast algorithm source code

AR 模型拟合，解决多变量自回归 (AR) 模型的参数估计问题-AR model fitting, since the settlement multivariable regression (AR) model parameter estimation problems

用仿生模式识别来训练目标，在视频序列中跟踪目标 function [sausage, num] = hypersausage_construct(P) %按照样本给定的顺序去求解超香肠神经元 [~, W] = size(P);%W是训练样例的个数 sausage = []; for i = 2:W     temp = power_two(P(:, i - 1), P(:, i));%构建第i-1个神经元  //temp是一个行向量     %temp = power_three(P(:, i - 2), P(:, i-1),P(:,i));     sausage = [sausage temp]; end sausage = [sausage P(:, end)]; num = (size(sausage, 2) - 1) / (W - 1);

应用背景该算法利用演化博弈的思想进行多小区用户的资源分配，将小区重叠部分当做种群，种群中的用户进行演化博弈进行网络切换，基站为其分配子信道。关键技术本算法利用matlab进行仿真测试，仿真结果显示演化博弈能够达到稳定，提升系统吞吐量，在小区资源分配能够有一个很好的参考。不同于传统的资源分配方法，可以给出一个新思路。