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Use the MATLAB randn function to generate 1000 points for x. Generate the output of the unknown system with the ?lter function and b=[1232 1] and a=[1]. Normalise the ?lter output so that its variance is unity, i.e. y = y./sqrt((sum(b.*b)); call the randn function again to generate 1000 points for the measurement noise, scale the values by 0.1 and add them to [ ], and calculate the Signal-to-Noise Ratio (SNR) in dB for y[k] (The power of zero mean white noise is 2 ; when a noise signal is scaled its standard deviation, i.e , gets scaled by the same factor).
- Use the xcorr function to estimate the cross-correlation and autocor relation elements to form Rxx and Pzx.
- Solve for the optimum Wiener ?lter. Is it close to that of the unknown system?
- Repeat the experiment by varying the scaling applied to the additive noise to 1.0 and 10.0, re-calculate the SNR for each case. What is the effect upon the Wiener solution? What happens if w is assumed to be greater than 4?
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log4x + logx=8
Compare results/performance with tridiagonal Gaussian elimination solver for the problem arising from -y''=f on (0,1) with y(0)=0=y(1). You may also need to use sparse storage an
1) Identify an equation that describes some chemical process. Your equation should have at least two parameters, at least one of which should contribute in a non-linear way. He
Illustration of script Documentation: For illustration, the script to compute the area of a circle could be modified to have comments: The first comment at the startin
Find f(t) for each F(s): Problem: Based on an examination given to a large class in which the maximum score is 100 points, assuming that 20 grades taken at random f
How can I separate a row vector into groups.
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Perform the convolution of following sequences (a) x[n] = [1 2 3], N1 = 1 and h[n] = [1 - 1], N2 = 1 (b) x[n] = [1 2 3], N1 = 2 and h[n] = [1 - 1], N2 = 1 (c) x[n] = [1 2 3], N1 =
using 0de 45 how can i get the anlytical and numerical solutions for an equation,,
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