2. The random variable z describes the observation of a physical phenomenon whose statistical description depends of one of two hypotheses. Conditioned on hypothesis H₁, the random variable z is Gaussian (200,10), while conditioned on hypothesis Ho, the random variable z is Gaussian (150,10). If Pr{H}=0.1, and Pr{H}=0.9, a) develop the likelihood ratio to implement a MAP decision test in order to decide between the two hypotheses. b) Obtain the probability of error of the test. c) If z=165, what decision results from the test?

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2. The random variable \( z \) describes the observation of a physical phenomenon whose statistical description depends on one of two hypotheses. Conditioned on hypothesis \( H_1 \), the random variable \( z \) is Gaussian \((200, 10)\), while conditioned on hypothesis \( H_0 \), the random variable \( z \) is Gaussian \((150, 10)\). If \( \text{Pr}\{H_1\} = 0.1 \), and \( \text{Pr}\{H_0\} = 0.9 \):

a) Develop the likelihood ratio to implement a MAP decision test in order to decide between the two hypotheses.

b) Obtain the probability of error of the test.

c) If \( z = 165 \), what decision results from the test?
Transcribed Image Text:2. The random variable \( z \) describes the observation of a physical phenomenon whose statistical description depends on one of two hypotheses. Conditioned on hypothesis \( H_1 \), the random variable \( z \) is Gaussian \((200, 10)\), while conditioned on hypothesis \( H_0 \), the random variable \( z \) is Gaussian \((150, 10)\). If \( \text{Pr}\{H_1\} = 0.1 \), and \( \text{Pr}\{H_0\} = 0.9 \): a) Develop the likelihood ratio to implement a MAP decision test in order to decide between the two hypotheses. b) Obtain the probability of error of the test. c) If \( z = 165 \), what decision results from the test?
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