Question: Using the MATLAB function awgn, repeat the recursive least-squares estimation of Example 10.4 when the output is corrupted by a white Gaussian noise with 10.0

Using the MATLAB function awgn, repeat the recursive least-squares estimation of Example 10.4 when the output is corrupted by a white Gaussian noise with 10.0 dB SNR. Compare the estimation results with those for 1.0 dB SNR.

Example 10.4

Consider the input and output data of a LTI system with sampling time T = 0.1 s: k 0 1 2 3 4 5 6 u(k) 1 1 1 1 1 1 y(k) 0 1.0000 0.9000 0.7100 0.7490 0.7831 0.7719

We wish to generate the least-squares estimate of the transfer function from the given input–output data. For this one may write a simple MATLAB code using the function arx as follows. y=[0; 1; 0.9; 0.71; 0.749; 0.7831; 0.7719]; u=ones (length (y), 1); T=0.1; % Create a data object using the

k 0 1 2 3 4 5 6 u(k) 1 1 1 1 1 1 y(k) 0 1.0000 0.9000 0.7100 0.7490 0.7831 0.7719

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