Probability, Random Processes, and Estimation Theory for Engineers

applies assume average becomes called Chapter coefficients complex compute conditional Consider consists constant continuous convergence correlation function decision defined definition denote density derivative determine differential discussed distribution equal Equation error estimate event Example exists expectation fact Figure filter function fx(x fy(y fz(z Gaussian given Hence important independent input integral interval involving joint known limit linear linear system Markov matrix mean mean-square measure noise normal observations obtain operator orthogonal outcomes output parameter pdf's Poisson positive probability problem Proof properties random process random sequence random variables random vector region respectively result sample satisfies sense shown in Figure signal solution solve space stationary Theorem theory tion variance write zero