登录
首页 » matlab » FrequencyIndependentandFrequencyDependentNonlinear

FrequencyIndependentandFrequencyDependentNonlinear

于 2010-03-12 发布 文件大小:441KB
0 150
下载积分: 1 下载次数: 21

代码说明:

  这是saleh提出其高功率放大器模型的原文 很难找 给大家共享(This is saleh to present its high-power amplifier model of the original hard to find for everyone to share)

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

  • OptimalStateEstimation
    涵盖了多种卡尔曼滤波算法及MATLAB实现(书内附有一些例子的源M文件),作者将多年的工作经验融入此书,使之成为学习卡尔曼滤波的同学一本不可多得的经典参考书。(The book content is very comprehensive, covering a wide range of Kalman filter algorithm and MATLAB implementation of many years of work experience will be integrated into the book, making the students learn a Kalman filter rare classic reference book.)
    2010-09-11 16:17:11下载
    积分:1
  • Wavelets
    小波去噪的分解与重构示例,里面附带数据文件(Wavelet Denoising sample decomposition and reconstruction, which attached to data files)
    2009-05-02 14:27:59下载
    积分:1
  • matlabcontrol
    几个控制理论的小程序,可以方便学习自动控制理论这门课(Can easily end the camera to the image transmitted matlab program for the software called.)
    2010-05-06 01:30:41下载
    积分:1
  • wannnpid
    基于小波神经网络辨识的PID神经模型源程序(wavelet-based neural network identification of the source of PID neural model)
    2006-06-03 20:34:52下载
    积分:1
  • 1996-Nonlinear_Systems
    本书为经典的非线性系统书籍,1996年出版。(This book is a classic nonlinear system books, published in 1996.)
    2013-04-08 21:17:02下载
    积分:1
  • lmirank
    说明:  一个强大的优化计算程序包,希望多大家有帮助(A powerful optimization package, I hope more people help)
    2011-03-23 14:47:02下载
    积分:1
  • MdLogic_2012
    source code identification using matlab
    2013-03-21 13:44:55下载
    积分:1
  • neWAC
    Wide Area Control Example
    2014-12-22 19:21:54下载
    积分:1
  • 端点检测
    用matlab实现短时能量和过零率的端点检测,并显示波形(using Matlab to achieve short-term energy and zero rate of endpoint detection and waveform display)
    2005-05-17 21:59:54下载
    积分:1
  • LNCPSO
    希望给辛苦科研的人带来一点点帮助--学习因子可以变化的PSO算法,不再是c1=c2=2,粒子进化更加灵活,下面是学习因子同步变化的pso,调用形式为[xm,fv]=LNCPSO(fitness,N,cmax,cmin,w,M,D)(People who want to work hard to bring a little bit of research to help- learning factor can vary PSO algorithm is no longer c1 = c2 = 2, particle evolution is more flexible, learning factor is below synchronous changes pso, calling in the form of [xm, fv] = LNCPSO (fitness, N, cmax, cmin, w, M, D))
    2013-09-23 19:15:32下载
    积分:1
  • 696516资源总数
  • 106425会员总数
  • 12今日下载