登录
首页 » matlab » arnold

arnold

于 2012-05-22 发布 文件大小:748KB
0 187
下载积分: 1 下载次数: 6

代码说明:

  arnold加密算法的matlab实现,arnold加密算法的matlab实现(arnold encryption algorithm matlab implementation)

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

  • progs-saeed
    These are the Matlab programs discussed in Craig Burnside, Discrete State-Space Methods for the Study of Dynamic Economies, in Ramon Marimon and Andrew Scott, eds. Computational Methods for the Study of Dynamic Economies. Oxford: Oxford University Press, 1999.
    2010-11-20 23:36:33下载
    积分:1
  • Desktop1
    afhkds lsfjk sd jsk nff lakd f
    2014-09-11 14:06:07下载
    积分:1
  • ch11_1
    利用类处理异常,实现根据异常处理规则,进行异常捕获(The use of unusual types of processing to achieve exception handling in accordance with rules capture abnormal)
    2009-04-12 17:20:13下载
    积分:1
  • MATLAB
    说明:  本书中包含有 所有MATLAB的函数中文简介 对英文不好的朋友 有很好的用处(This book contains all the MATLAB functions Introduction to the English is not good Chinese friends have a good use)
    2010-04-25 16:28:11下载
    积分:1
  • buckboost
    buck/boost双向DCDC变换电路,即可以进行降压也可升压,采用双闭环控制(buck/boost bi-directional DC DC converter circuit, both can also be buck boost, dual loop control)
    2020-07-04 16:40:02下载
    积分:1
  • tabu-search-matlab
    求解VRP 问题的智能算法 禁忌搜索算法MATLAB源代码(tabu-search MATLAB code of VRP )
    2015-07-02 19:53:02下载
    积分:1
  • MATLAB-Codes-for-FEA
    Matlab在有限元中的应用经典教程,从结构动力学基本方程到编程方法(Matlab tutorials in classical finite element the basic equation of structural dynamics to the programming method)
    2016-04-24 16:14:14下载
    积分:1
  • handout24
    英文描述特征值 的计算 定义 便于理解 为矩阵运算提供 帮助(eigenvalue)
    2010-10-21 16:13:00下载
    积分:1
  • hmm
    隐马尔科夫模型,matalb实现,比较好的(Hidden Markov Model, matalb achieved relatively good)
    2008-03-31 21:45:05下载
    积分:1
  • fit_ML_normal
    fit_ML_normal - Maximum Likelihood fit of the normal distribution of i.i.d. samples!. Given the samples of a normal distribution, the PDF parameter is found fits data to the probability of the form: p(r) = sqrt(1/2/pi/sig^2)*exp(-((r-u)^2)/(2*sig^2)) with parameters: u,sig^2 format: result = fit_ML_normal( x,hAx ) input: x - vector, samples with normal distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields sig^2,u - fitted parameters CRB_sig2,CRB_u - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML
    2011-02-09 19:09:33下载
    积分:1
  • 696516资源总数
  • 106562会员总数
  • 4今日下载