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subcarriers in the j-th sub-band can be devised by calculating the expected overall bit error probability for all available modulation modes Mn in each sub-band, which is denoted by Fe ( n )= l/Ns p e ( ~ jAdn). For each sub-band, the mode having the highest throughput, , whose estimated BER is lower than a given threshold, is then chosen. While the adaptation granularity is still limited to thesub-band width, the channel quality estimation includesnot only the most corrupted subcarrier, which leadsto an improved throughput. Figure 13.20 shows the BER and throughput performance for the 16 subband adaptive OFDM modem employing the BER estimator adaptation algorithm in the Rayleigh fading time dispersive channel of Figure 13.3. The two sets of curves in the figure correspond to and lop1, respectively. Comparing the modem'sperformance target bit errorrates of for a target BER of lop2 with that of the "speech' modem in Figure 13.18, it can be seen that the BER estimator algorithm results significantly higher throughput, while meeting the in BER requirements. The BER estimator algorithm is readily adjustable to different target bit error rates, which is demonstrated in the figure for a target BER of 10-l. Such adjustability is beneficial, when combining adaptive modulation with channel coding, as will be discussed in Section 13.6.5.

From the 2M x 1 vector anwe can recover estimates for the coefficients of { L k ( z ) } ; they are simply stacked on top of each other in En. Specifically, from (28.9), the update for the estimate of the k-th weight vector 1k is given by (in terms of the k-th entry of e;B,n and the k-th regression vector u ; , ~ ) :

. . ,1}.

FIGURE 9-47

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Other ways of identifying fraud risk factors include studying past frauds and allegations of fraud in the company, frauds in the industry, unusual nancial trends or relationships identi ed from analytical procedures, and the potential role weak IT controls could play in enabling fraudulent activity to occur. For companies with more than one operating unit, the process would desirably consider fraud risk factors at the entity level as well as in signi cant operating units or segments.

When you convert the image to Polar Coordinates (by selecting the Rectangular to Polar option in the Polar Coordinates dialog box), you look down on it from an extreme aerial view. This means that the entire length of the image becomes a single dot in the exact center of the polar projection. If you select the Polar to Rectangular option, the Polar Coordinates filter produces the opposite effect instead of the entire image becoming a dot in the center of the project, the image flows from a polar center outward, in a rectangular shape. Figure 11.30 gives you a little food for thought.

The discipline of radiometry focuses on measuring the energy content of optical radiation and on mapping the ow of energy through optical systems. Radiometry describes the optical eld using phenomenological functions related to the irradiance such as the spectral radiance, Bn (x, s, n), which is the power radiated through point x [ R3 in direction s [ S2 per unit solid angle per unit wavelength. The SI unit of spectral radiance is watt per steradian per square meter per hertz. The spectral radiance may be integrated along the wavelength axis to produce the radiance, which is the radiant energy propagating through x in the s direction per unit solid angle. This section discusses the relationship between the spectral radiance and the crossspectral density and describes the constant radiance theorem, which limits the ability of optical systems to focus partially coherent light. Unless otherwise indicated, the term radiance refers to the spectral radiance in subsequent discussion. 6.7.1 Generalized Radiance

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