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where the minimum is over all linear predictors b and the maximum is over all densities f satisfying R0 , . . . , Rp . 12.8 Maximum entropy characteristic functions. We ask for the maximum entropy density f (x), 0 x a, satisfying a constraint on a the characteristic function (u) = 0 eiux f (x) dx. The answers need be given only in parametric form. a (a) Find the maximum entropy f satisfying 0 f (x) cos(u0 x) dx = , at a speci ed point u0 . a (b) Find the maximum entropy f satisfying 0 f (x) sin(u0 x) dx = . (c) Find the maximum entropy density f (x), 0 x a, having a given value of the characteristic function (u0 ) at a speci ed point u0 . (d) What problem is encountered if a =

Copper is costly. Thus many telecommunication companies employ gauges with diameters no greater than 22 gauge.

hen you design a movie, chances are sound will be included. The vast majority of Web surfers seem to expect sound as a given with any Flash design. However, not everyone likes sound when viewing a Web site. And not everyone likes the same type of music. Therefore, it is necessary to provide some type of control the viewer can use to control the sound. And that job is left to you, the designer of the movie. Soundtracks can be incorporated in the document Library, or you can add a soundtrack at runtime. In this chapter, you ll learn to create a movie with nothing but a soundtrack that is loaded into another movie. You ll also learn to create an instance of the ActionScript Sound object. When you create an instance of the Sound object, you can use methods of the Sound object to control the volume of the sound, pan the sound between speakers, or start and stop the sound. When you complete the chapter project, you ll know how to create a working sound controller.

Figure 3.1 A plane approximates the linear relationship between one response and two continuous predictors.

purposes, one needs, as discussed in previous chapters, very good synchronization, because the resulting localization is directly linked to it. Nevertheless, some methods have been proposed, as shown in 4. Owing to the poor time accuracy in telecommunication networks, the resulting accuracy is around 100 m outdoors. When multipath occurs, and multipath occurs very often in telecommunication networks, the accuracy drops dramatically to a few hundred meters. Indoor positioning is also affected by this phenomenon, although similar accuracies are often reported for both outdoors and indoors. The global characteristics of a TOA-based positioning system are summarized in Table 9.15 (typical outdoor performances). The TDOA method is very similar and results are equivalent. The Matrix system (refer to 4) reported a typical accuracy of around 100 m. The global characteristics of a TDOA-based positioning system are summarized in Table 9.16. This technique could also be used indoors, but because of the same limitations as for TOA and AOA, the results are not acceptable. An advantage of this technique compared to TOA is the possibility, at no expense, of implementing it directly at the terminal end. This brings it closer to GNSS approaches.

Propagation conditions, due to path loss and fading appearance User mobility when the mobile approaches the cell boundary, the cochannel interference at the mobile increases Traffic load if more users share the same channel, cochannel interference in the system increases Moreover, it is important to spread channels within individual cells as far as possible Careful design in order to avoid the appearance of intermodulation effects should also take place Frequencies should be established such that no significant intermodulation products from any combination of cosited transmitter frequencies fall on any other channel in use in that vicinity This usually implies third- and fifth-order compatibility In densely populated areas, this strategy is difficult to implement completely, but in order to avoid unwanted mobile receiver outputs resulting from interference, implementation of at least third-order compatible frequency plans is highly desirable 3.

5 CHANNEL ASSIGNMENT Channel assignment is a fundamental task of resource management that increases the fidelity, capacity, and quality of service of cellular systems by assigning the required number of channels to each cellular region in such a way that both efficient frequency spectrum utilization is provided and interference effects are eliminated The channel allocation strategy can be seen as a method of assigning available channels to calls originating in the cells If the strategy is unable to assign a channel, the call is blocked The basic goal to be achieved by channel allocation techniques under the prism of the rapidly growing demand for cellular mobile services is to efficiently utilize the available spectrum so as to achieve optimum system performance The main focus on research concerning channel assignment is to find strategies that give maximal channel reuse without violating the constraints so that blocking is minimal.