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GYH

于 2014-09-22 发布 文件大小:1KB
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代码说明:

  实现MATLAB的自适应滤波器代码,LMS的改进,分析其收敛性(MATLAB realization)

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  • myDFT
    This function is equivalent to matlab fft2 function, but without using for loops, instead this function is implemented using matrix multiplication.
    2012-03-26 20:21:50下载
    积分:1
  • matlabdrawaFFT
    简单易用的matlab FFT程序,零频在中间,另外还经常用的matlab绘图代码列了出来(Simple and easy-to-use program matlab FFT, zero frequency in the middle, is also often used matlab drawing code out)
    2013-01-29 10:45:54下载
    积分:1
  • XYNTServiceProject
    good code good code good code good code good code good code good code good code good code (good code good code good code good code good code good code good code good code good code)
    2007-11-23 01:36:05下载
    积分:1
  • matlab
    matlab基本信息参考资料,包括直方图均衡等等(matlab basic information reference materials, including histogram equalization, etc.)
    2011-05-16 16:16:15下载
    积分:1
  • DSPzuoye
    自己的数字信号处理第三版的课后实验作业,有兴趣的可以参考参考。(Its own digital signal processing of the third edition of the after-school lab assignments, who are interested can refer to reference. !)
    2012-05-06 13:18:36下载
    积分:1
  • matlab
    巴特沃斯滤波器,主要实现的是低通信号,此功能模块的低通曲线很符合理想的幅频特性。(Butterworth filter, the main achievement is low traffic numbers, the low-pass curve is consistent with this function module ideal frequency characteristics.)
    2014-01-26 09:45:02下载
    积分:1
  • NM
    说明:  Newton法的计算程序,通过它可以计算复杂函数的根(Newton method computer program, through which the roots of complex functions can be calculated )
    2010-12-30 14:19:22下载
    积分:1
  • MPC
    预测控制方法----------------------(Predictive Control----------------------)
    2010-02-01 19:38:13下载
    积分:1
  • matlab-SIMO-control
    微机控制系统大作业单输入单输出,多输入单输出控制matlab程序,(The microcomputer control system project single input and single output, many input single output control matlab, )
    2011-07-17 18:01:56下载
    积分:1
  • RICE-UNIVERSITY
    标准压缩感知(CS)理论决定了可靠的信号恢复是可能给M= O(KLOG(N / K))的测量。我们证明了它可以通过利用超越简单的稀疏性和可压缩性由包括价值观和信号系数的位置之间的依赖关系更加逼真信号模型大大降低Mwithout牺牲的鲁棒性。(The standard compressive sensing (CS) theory dictates that robust signal recovery is  possible from  M=O(Klog(N/K))  measurements. We demonstrate that it is possible to substantially  decrease  Mwithout sacrificing robustness by leveraging more  realistic signal models that go beyond simple sparsity and  compressibility by including dependencies between values and  locations of the signal coefficients.   )
    2014-01-06 20:07:54下载
    积分:1
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