Y1 has zero mean and covariance matrix Y2 The random vector Y = %3D 2 Cy...

 

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Y1 has zero mean and covariance matrix Y2 The random vector Y = %3D 2 Cy 2 Determine the linear, minimum-mean-square-error (LMMSE) estimate YLMMSE = AX +b of Y, based on the %3D scalar measurement X = "Y, (1) C = In other words, find a (2 x 1) matrix A and a (2 x 1) vector b such that E||| Y – AX – b|PI E (Y - AX – b)" (Y– AX – b), is minimized, where X is as given in (1). Y1 has zero mean and covariance matrix Y2 The random vector Y = %3D 2 Cy 2 Determine the linear, minimum-mean-square-error (LMMSE) estimate YLMMSE = AX +b of Y, based on the %3D scalar measurement X = "Y, (1) C = In other words, find a (2 x 1) matrix A and a (2 x 1) vector b such that E||| Y – AX – b|PI E (Y - AX – b)" (Y– AX – b), is minimized, where X is as given in (1).