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于 2009-04-08 发布 文件大小:1KB
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说明:  GM(1,1)模型程序 可用于一般时间序列预测(GM (1,1) model program can be used for general time series prediction)

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  • 11
    说明:  粒子群工具箱,非常好的源程序,很好用。。。(Particle swarm optimization toolbox, a very good source, a very good use. . .)
    2009-12-16 16:49:24下载
    积分:1
  • LFM_single_pulse
    线性调频信号的产生程序,比较简单的一种,用来仿真参考。还有个127位m序列的产生程序(Linear FM signal generation process, a relatively simple to simulate reference. There is a 127 m sequence generation program)
    2011-07-21 11:42:31下载
    积分:1
  • CustomHighPassFiltering
    this filter allows high frequency
    2015-01-03 01:54:43下载
    积分:1
  • FEI
    假设在一个ad hoc网络中,移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道,测量接收到的信号功率X,其中X= I + N, I为接收到的干扰,N是噪声。移动节点只有在X<INThre时,才可以发射。式中,INThre为背景噪声门限。 在仿真中,我们规定每个移动节点的发射功率是常数,PTx = 1W;接收节点接收机的灵敏度Smin = -80 dBm;信号质量 min = 2 dB;系统的背景噪声门限INThre = 1.2e-10。 (Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality )
    2008-01-05 11:21:40下载
    积分:1
  • Face_test_luminance
    face detection matlab easy
    2010-02-21 06:42:36下载
    积分:1
  • montcarlo
    Z transformation montcarlo module
    2014-09-19 16:59:33下载
    积分:1
  • 粒子群算法综合线阵低副瓣方向图
    说明:  粒子群算法阵列优化,对阵列方向图的综合,实现低副瓣阵列方向图(Particle swarm optimization (PSO) algorithm for array pattern synthesis to achieve low sidelobe array pattern)
    2020-11-02 11:19:53下载
    积分:1
  • agh_chapter03
    lagre no of m file for matlab course code file #2(lagre no of m file for matlab course code file#2)
    2009-05-07 23:59:24下载
    积分:1
  • RankMethod
    实现matlab做排行之功能,遇到同分排名之数值可编为同样名次(Top realize matlab function to do, faced with the numerical ranking points can be made available for the same position)
    2008-07-02 21:59:48下载
    积分:1
  • source
    This derivation of the normalised least mean square algorithm is based on Farhang- Boroujeny 1999, pp.172-175, and Diniz 1997, pp 150-3. To derive the NLMS algorithm we consider the standard LMS recursion, for which we select a variable step size parameter, μ(n). This parameter is selected so that the error value , e+(n), will be
    2011-01-12 17:04:12下载
    积分:1
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