11. Let x [n] be real WSS with correlation r [m] which is assumed known. The...
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11. Let x [n] be real WSS with correlation r [m] which is assumed known. The second order prediction is formulated as follows. Define e [n] via: e [n] = x [n] + a₁x [n 1] + a₂x [n- 2] We want to find the coefficients a₁, a2 such that e [n] 1 x [n 1] and e[n] x [n-2]. Formulate each condition as an appropriate expectation, and simplify to obtain two lin- ear equations in the two unknowns a₁, a2, where the coefficients in the linear equations are appropriate values of r [m]. 11. Let x [n] be real WSS with correlation r [m] which is assumed known. The second order prediction is formulated as follows. Define e [n] via: e [n] = x [n] + a₁x [n 1] + a₂x [n- 2] We want to find the coefficients a₁, a2 such that e [n] 1 x [n 1] and e[n] x [n-2]. Formulate each condition as an appropriate expectation, and simplify to obtain two lin- ear equations in the two unknowns a₁, a2, where the coefficients in the linear equations are appropriate values of r [m].
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Related Book For
Probability and Random Processes With Applications to Signal Processing and Communications
ISBN: 978-0123869814
2nd edition
Authors: Scott Miller, Donald Childers
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