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Unformatted text preview: 1 . 5 1 v Solve (analytically, using pencil and paper) for the noise covariance matrix, E v v T . Simulate the model using v in place of v . Solve for x using 1 weighted least squares. What did you use for the weight matrix? Calculate an estimate of the error covariance matrix and compare it to the theoretical value, as in part 2 above. 4. How would you (numerically, using Matlab) conFrm that weighted least squares works better than unweighted least squares for the correlated noise vector of part 3? Explain your idea in your report and demonstrate it in Matlab code. 2...
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This note was uploaded on 01/15/2012 for the course EEL 6935 taught by Professor Staff during the Fall '08 term at University of Florida.
- Fall '08