登录
首页 » matlab » mfiles

mfiles

于 2011-10-12 发布 文件大小:17KB
0 185
下载积分: 1 下载次数: 4

代码说明:

  vessel models and control engg

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • eucdist
    two methods of calculating eucledian distance are shown in the m files
    2009-03-13 23:58:29下载
    积分:1
  • DVB-Tsimulation
    in this projeh DVB-T signal can simulate by matlab
    2013-07-10 23:17:41下载
    积分:1
  • simple-bp
    一个简单的bp算法,运行中可以看到每一步的结果。适合初学者。(A simple BP algorithm, the operation can be seen in the results of each step. Suitable for beginners.)
    2014-11-06 11:14:23下载
    积分:1
  • Smith
    传输线的工作状态波形,包括行波和驻波,当参数改变时,传输线的工作状态也因此而改变(The operating state of the waveform of the transmission line, including traveling wave and standing wave, when the parameter is changed, the working status of the transmission line can also be changed)
    2013-04-29 16:06:28下载
    积分:1
  • chap12
    MATLAB应用大全一书的配书光盘第十二章源代码,该文件夹收录了本书涉及的源文件。收录了一些优秀应用实例信息,便于读者学习了解。(MATLAB application of CD attached with books of chapter 12 source code, this folder contains the book files. Includes some excellent examples of application information, convenient for readers to learn. )
    2014-01-17 10:57:39下载
    积分:1
  • pso
    matlab pso algorithm code that can use easily
    2014-02-04 15:56:12下载
    积分:1
  • BIHT-l1
    为了解决二进制CS而编写的算法,使用了用l1范数最小化(an algorithm for binary CS,use l1 norm)
    2012-03-29 19:24:32下载
    积分:1
  • MATLABduomubiaoyouhua
    matlab多目标优化问题实现,可以参考一下啊(matlab multi-objective optimization, you can refer to ah)
    2010-01-17 17:19:07下载
    积分:1
  • roots-by-gauss-siedel
    this code helps to find roota of equation by gauss seidel method
    2014-12-24 02:06:45下载
    积分:1
  • gongetidufadshuzhixingzhi
    共轭梯度法(Conjugate Gradient)是介于最速下降法与牛顿法之间的一个方法,它仅需利用一阶导数信息,但克服了最速下降法收敛慢的缺点,又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点,共轭梯度法不仅是解决大型线性方程组最有用的方法之一,也是解大型非线性最优化最有效的算法之一。 在各种优化算法中,共轭梯度法是非常重要的一种。其优点是所需存储量小,具有步收敛性,稳定性高,而且不需要任何外来参数(Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters numerical experiment, this is the modern scientific computing of the answer above problem sets)
    2012-03-26 18:48:46下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载