Now assume two independent complex random variables z, and z2. Each one of them is Gaussian withzero mean and variance o² = 1 \text { a. What is the mean vector and covariance matrix of the vector } z=\left[\begin{array}{l}

z_{1} \\

z_{2}

\end{array}\right]

С.In part (b), you calculated E(y). Which one of the following is correct: \text { i. } E(v)=e^{j \theta} E(z) \text { ii. } E(y) \neq e^{j \theta} E(z) d. In part (c), if the correct answer is (i) then the vector z is called circular symmetric vector. If the correct answer is (ii) then the vector z is not circular symmetric vector. Read through the Appendix A to learn more about this statement.