University of North Florida

University of North FloridaElectrical Engineering Program

EEL 4657Linear Control Systems Laboratory

Dawn Owens(N00152181)Lab 5 Least-Squares Estimation of Linear Multi-Parameter Models

Abstract: The objective of this lab was to continue generalizing the insights from previous labs to input-output models that involve more than just one parameter to be estimated. Characterizing the accuracy of a multi-parameter predictor required utilizing fundamental statistical concept called the covariance, which is essentially a measure of the correlation between two random variables. Using the simplest setting of a two-parameter predictor, MATLAB will be used (i) to show that correlation between the two parameters can be influenced by the choice of input data and (ii) to examine the influence of the number of model parameters on second-order statistics.

Exercise L6-1 (Characterizing the Accuracy of a Two-Dimensional Parameter Estimate)

StatisticExperiment 1Experiment 2

Mean VectorE[1] = -3.71 x 10-4E[2] = 9.99 x 10-2E[1] = 5.0 x 10-4E[2] = 9.99 x 10-2

1