sv_chnl

Ebook Digital Signal Processing (An Introduction with MATLAB and Applications)

本书荣获2005年第十五届Jolt通用类图书震撼大奖。 继 Effective C++ 之后，Scott Meyers 于 1996 推出这本「续集」。本书与现今之 C++ 标准规格几乎相同。可能变化的几个弹性之处，Meyers 也都有所说明与提示。(the book won the 2005 session of the 15th General Books Jolt Awards shock. Following the Effective C, Scott Meyers in 1996 to launch the "sequel." The book's C with the current standard is almost the same. Several possible changes in flexibility, Meyers also has suggested and described.)

经优化后的xls文件导入到dbf文件的表单,dbf文件请自己创建(By importing the XLS file after the optimization to the DBF file form, please create your own DBF file )

针对33节点编写的潮流程序,运用前推回代法，实用性很强(Flow program written for 33 nodes, use push backward substitution method very practical)

遗传算法GA—模拟自然界遗传机制和生物进化论而成的一种并行随机搜索最优化方法。（具有“生存+检测”的迭代过程的搜索算法）基于自然界“优胜劣汰，适者生存”的生物进化原理引入优化参数形成的编码串联群体中，按照所选择的适应度函数并通过遗传中的选择、交叉和变异对个体进行筛选，使适应度值好的个体被保留，适应度差的个体被淘汰，新的群体既继承了上一代的信息，又优于上一代。反复循环，直至满足条件。(GA-A parallel random search optimization method that simulates natural genetic mechanisms and biological evolution. (Search algorithm with "survival + detection" iterative process) Based on the biological evolution principle of "survival of the fittest, survival of the fittest" in the natural world, the coding series formed by optimized parameters is introduced. Individuals are screened according to the selected fitness function and through genetic selection, crossover, and variation, so that individuals with good fitness values are retained, individuals with poor adaptability are eliminated, and new groups inherit the information of the previous generation., Better than the last generation. Repeat until conditions are met.)

this MATLAB Script simulate Poiseuille_flow and compare the result with analytical answer

自己编写的ga（遗传算法）matlab工具箱。对比过，速度挺快的。(I have written ga (genetic algorithm) matlab toolbox. Been compared, the speed very fast.)

feature selection demo

Source Code for bag of features, developed in Matlab

Programming Matlab and C++,混合编程；经典教程；