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Multipath associativity based routing (MPABR), 383 reactive routing, 383 protocol comparisons, 423t, 424t Multipath coef cients estimation, 163 Multipath components (MPCs), 184 clustering, 187 phenomenon, 193 Multipath effects propagation mechanisms, 185f Multipath propagation, 93 94 UWB geolocation, 52 Multiple access interference (MAI), 4, 14, 95 mitigation in UWS, 227 248 at receiver side, 231 243 signal model, 228 229 at transmitter side, 244 248 UWB geolocation, 53 Multiple ad hoc networks. See Mobile ad hoc networks (MANETs) Multiple CTA (CTA-M), 303 Multiple orthogonal pulse, 104 design, 123 124 Multipoint relay (MPR), 355 selectors, 358 Multiresolution approach, 36 Multistage block-spreading UWB access MAI mitigation, 247 Multistage Wiener lter (MSWF), 244 MultiWARP. See Multihop wireless ad hoc routing protocol (MultiWARP) NACF. See Normalized autocorrelation function (NACF) Nakagami distributions, 197, 217 Nakagami frequency selective fading, 216f Nakagami-m factor, 197 Narrowband antenna systems system transmission ef ciency, 147f Narrowband channel models, 6, 183, 196 Narrowband interference (NBI), 4, 255 271, 256 avoiding, 261 266 canceling, 267 271 jamming resistance DSSS systems, 258 robustness, 126f scenario for multicarrier modulation systems, 262f NBI. See Narrowband interference (NBI) NCD. See Neighbor-changing degree (NCD) NDMR. See Node-disjoint multipath routing (NDMR)

A schematic of the situation being considered, that of a laser diode operating in an external cavity, is shown in Figure 2.7. The iterative scheme used to analyse the system shown in Figure 2.7 is based on a perturbation approach. The unperturbed state is assumed to be that of a solitary laser and the perturbation is provided by optical feedback and noise. A reference plane is defined just inside the right-hand laser facet at z = 0. A+ t is the right-moving field passing the laser facet of field reflectivity, r2 . A (t ) is the left-moving field re-entering the laser diode and is the external cavity round-trip time. This approach is based upon the work of Mork [29]. The iterative single mode equations may be extended to include multiple longitudinal modes by assuming that the angular mode frequencies of the solitary laser are:

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ust because your item doesn t sell the first time you put it up for sale on eBay doesn t mean your item will never sell. Quite honestly, putting an item up for sale for one week really doesn t give it the exposure it may need. If someone has been looking for an item for years, what are the chances that he or she looks at eBay that very week that you have listed it In this chapter, I show you how to relist your item and give it another week s exposure. If that still doesn t work, don t be discouraged: your item may need more than two weeks exposure before it will sell. An eBay store gives your items a lot more exposure for a reasonable price. This chapter shows you how to set up an eBay store and discusses the different bells and whistles available. Finally, for those few items that will never sell on eBay (not at auction and not in your store), this chapter discusses your options for disposing of them.

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Before continuing our discussion, it is very important to understand that this section is not making a value judgment on contextual versus noncontextual modeling, as both are useful. It is not a question of better or worse, but a question of whether your specific application is better served by fixing the context or not fixing the context. In some ways this is the classic trade-off between flexibility in the face of change versus reliable execution via static processes. For many applications, fixing the context at the document level is the best method. One example of this would be high-volume static transactions between wellknown trading partners. When the environment is stable and the volume is high, it is both easier and more efficient to strictly fix the context of documents and messages to reduce errors and increase throughput. Of course, the opposite situation, where neither the environment is stable nor the volume is high, is the classic example where flexibility and noncontextual modeling are the best choice. We will examine more situations where noncontextual modeling is applicable in the following paragraphs.

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