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Building applications with Mono

基于Matlab的电力系统潮流编程计算,简洁实用，电力系统专业(the program of power system load flow)

Hough检测直线,圆,椭圆的代码 其中椭圆是用matlab(Hough line detection, round, oval ellipse code which is used Matlab)

说明：  rsa示例，实现了加密和解密的基本功能，供大家参考(rsa example, to achieve the basic functions of encryption and decryption, for your reference)

说明：  一个简单ARX画线, f f(a simple line drawing,)

特征值分析，便于模态分析电网稳定态态势分析和薄弱环节识别(Eigenvalue analysis, to facilitate modal analysis grid steady state trend analysis and identification of weak links)

the project is used for the customers to learn something(important)

Systemidentificcation，系统辨识 (Systemidentificcation, system identification)

C语言编的简单遗传算法程序 各项功能齐全(SGA-simple Genetic Algorithm)

调试所用Matlab版本是6.5，gatbx-toolbox是调试过程中使用的工具箱，有些热心的研友已经提供了该工具箱，之所以再贴一遍，是因为6.5版本下调试该工具箱会出现一些错误提示，在该版本中已经进行了改正，使用该工具箱只需要将压缩包下的gatbx和gatbxTest_fns加入到Matlab搜索路径即可，另外gatbx-origin是Sheffield大学提供的原始版本的工具箱，未做任何改动，两者可做比较之用 3.gatbx-example是算例调试源码和各算例的调试说明，大家可以对照原书进行比较 4.窃以为gatbx工具箱较之Matlab7新版下的gads工具箱更能让人熟悉和了解遗传算法的原理和计算过程，虽然在可视化方面不及gads 5.学习遗传算法如果首先用熟相关工具箱的话，能够先培养信心，然后更有兴趣去专研和了解具体的算法，如果就用现有的工具箱就能解决问题的话，不了解其详细的算法也未尝不可，毕竟不是每个研友都能向see_moonlight那样开发自己的工具箱吧, ( The debugging uses the Matlab edition is 6.5, gatbx-toolbox debugs the toolbox which in the process uses, somewhat warm-hearted ground the friend already to provide this toolbox, the reason that pasted again, was because under 6.5 editions debugged this toolbox to be able to present some wrong prompts, had already carried on the correction in this edition, will use this toolbox only to need to compress package of under gatbx and gatbx Test_fns joins to the Matlab search path then, moreover gatbx-origin was the primitive edition toolbox which the Sheffield university provided, has not made any modification, both might make the comparison are the example debugging sound code and various examples debugging explained with 3.gatbx-example, everybody might compare the original bookCarries on comparison 4. in my opinion under the gatbx toolbox s to be able to let the human compared with Matlab7 update gads toolbox be familiar with the understanding genetic algorithm principle and)