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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?
I want to know how to create a numerical solution code for analysing temperature/isotherms on a 2d square plate with a singular heat source and opposing edges being held at constan
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Analytical solution
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Creating row Vectors: There are many ways to generate row vector variables. The most important way is to put the values which you want in the vector in square brackets, separa
You are given data similar to the examples and sample problems in the statistics topic. Write MATLAB program to do the following: 1. Plot histogram, relative frequency histogram
Write a pseudo-code showing the list of steps to take for solving the given problem. In this process, you should identify the functions that are to be used in the program. Develop
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illustration of for loop: illustration, to print a column of numbers from 1 to 5: for i = 1:5 fprintf('%d\n',i) end This loop can be entered in the Command Wi
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