# ps2 - EE 806 Detection and Estimation Theory Apr 7 2008 OSU...

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Unformatted text preview: EE 806, Detection and Estimation Theory Apr. 7, 2008 OSU, Spring 2008 Due: Apr. 21, 2008 Problem Set 2 Problem 1 - MATLAB Exercise In this problem you will visually verify properties of the Bayes risk function r π ( δ π ) (referred to as V ( π ) in Poor). Once you have written your code, you should be able to investigate a variety of system parameters. You are encouraged to play with different system parameters. Consider the location testing problem with Gaussian error. Assume that μ =- 1 , μ 1 = 5 , σ 2 = 4. Furthermore, assume that you have the following cost matrix: C = . 1 1 . . 8 . 25 (a) Give an expression (or collection of expressions) for the Bayes risk function r π ( δ π ). (b) Plot this function and verify that it is concave and that the end points ( π = 0 and π = 1) of the function are the predicted values. (c) Determine (numerically if need be) the least favorable prior probability π L . For π L , evaluate R ( δ π L ) and R 1 ( δ π L ), where δ π L is the Bayes rule for...
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ps2 - EE 806 Detection and Estimation Theory Apr 7 2008 OSU...

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