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Consider again Ex. 1.2, where z is a BPSK signal that assumes the values 51 with probability 112. Let us verify that the estimator x = sign(y) is not optimal in the least-mean squares sense. We already know that this is the case because we found in Ex. 1.2 that the optimal estimator is t a n h ( y ) . Here we wish to verify the sub-optimality of sign(y) without assuming prior knowledge of the optimal estimator, and by relying solely on the orthogonality condition (1.12). According to Thm. 1.2, we need to verify that the estimator sign(y) fails the orthogonality test. I n particular, we shall exhibit a function g ( y ) such that the difference z - sign(y) is correlated with it. Actually, we shall choose g ( y ) = sign(y) and verify that (1.14) Let us first check whether the estimator k = sign(y) is biased or not. For this purpose we recall that y = z w and that

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which is shown in Fig. 15.20. Notice that S( w) is centered about lhe carrier frequency. This is the effect of modulation.

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Move To specific record is most often used in conjunction with a search routine or a master-detail application. n

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