By Robert A. Kleist, Theodore A. Chapman, David A. Sakai, Brad S. Jarvis

Radio frequency identity (RFID) know-how is shaping the way forward for worldwide offer chains, and shrewdpermanent retail customer items businesses are looking for possibilities for complicated compliance with mandates. The authors draw on their stories of operating with the industry's most sensible providers to Wal-Mart to prepared them for RFID adoption. They describe the way to start utilizing RFID and current a primer on shrewdpermanent label know-how. The e-book additionally bargains snapshots of what profitable RFID migration feels like, together with uncomplicated, rigorously charted steps in every one innovative part of deployment.

**Read or Download RFID Labeling: Smart Labeling Concepts & Applications for the Consumer Packaged Goods Supply Chain PDF**

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**Example text**

It is useful to demonstrate this property at this point, since it will be appropriate in dealing with multiple signal samples in the next section, in which case we shall find ourselves considering sums of logarithms of likelihood ratios. Consider, then, two extreme cases: 1. 'Y« 1: then r is likely to be small also, and 10 (r;) == 1 + (;~y == er'~/2N rA« 1 N (2-1-14) Taking the natural log, as in Eq. (2-1-13), r2'Y > 'Y > 2N 2N r2 or Thus, for small 'Y the (2-1-15) likelihood test reduces to that of using a quadratic STATISTICAL COMMUNICATION THEORY 53 envelope detector, and the output must exceed twice the mean-squared noise at the input.

C. r) Gx( f ) G~(f) : = Rx(r) s, (f ) Rx~(O):O The random variable x(t) and its Hilbert transform are thus uncorrelated at a given instant of FIG. 1-6-4. Hilbert-transform relatime. This is apparent from the fact that tions for a random process. since Rz('1') is even in '1', "R:t('1') must be odd, or "R:t(O) = o. This fact will be particularly useful in rederiving the envelope statistics of noise, using the Hilbert-transform formulation. d. (1-6-26) (1-6-27) Here Rt('1') represents the autocorrelation function of the analytic signal or preenvelope z(t) = x(t) + j£(t) (1-6-28) The proof of Eq.

The Fourier transform of z(t) is, from Eq. 5) (This represents the action of the phase shifter. ) 31 GENERAL TUTORIAL MATERIAL Introducing Eq. (1-6-5) into (1-6-4) we get, Z(w) = { ~X(w) w~O w