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DSP

于 2013-11-08 发布 文件大小:197KB
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  任务: 1) 借助MATLAB画出误差性能曲面和误差性能曲面的等值曲线(参考PPT2.1第17页的两幅图); 2) 写出最陡下降法以及LMS算法的计算公式(取 ); 3) 用MATLAB产生方差为0.05, 均值为0白噪音S(n),并画出某次采样得到的波形(即产生任意一个噪声随机序列); 4) 根据 2)中的公式,并利用 3)中产生的S(n),在 1)中的误差性能曲面的等值曲线上叠加画出采用最陡下降法以及LMS法时H(n)的在叠代过程中的轨迹曲线(参考PPT2.1第17页的右下图的曲线1和曲线2)。 5)用MATLAB计算并画出LMS法时 随时间n的变化曲线(对应S(n)的某一次的一次实现)和e(n)波形; 注意:某一次实现的结果并不能从统计的角度反映实验的结果 的正确性,为得到具有统计特性的实验结果,可用足够多次的 实验结果的平均值作为实验的结果。用MATLAB计算并画出 采用LMS法时,J(n)的100次实验结果的平均值随时间n的变 化曲线(即 生成随机噪声信号并计算结果,重复执行100次, 求平均结果)。 6)在 1)中的误差性能曲面的等值曲线上,叠加画出采用LMS法得到的100次实验中的H(n)的平均值的轨迹曲线; (Task: 1 ) Draw with MATLAB error performance surface and surface contour error performance curve ( refer PPT2.1 two chart on page 17 ) 2 ) Write the steepest descent method and the LMS algorithm formula ( take ) 3 ) Using MATLAB to generate variance of 0.05 with a mean of 0 white noise S (n), and draw a particular sampling waveform ( ie, any noise generated random sequence ) 4 ) based on 2 ) of the formula , and use 3 ) generated in S (n), in a ) the error performance curves superimposed on the surface contour plot using the steepest descent method and the LMS method when H (n) the iterative process in the trajectory curve ( refer PPT2.1 page 17 bottom right of the curves 1 and 2 ) . 5 ) using MATLAB LMS method is used calculate and draw the curve with time n (corresponding to S (n) of a first implementation of a ) and e (n) waveform Note : in a first implementation of the results are not reflected from a statistical point of view of accuracy of the experimental results ,)

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