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front that MOSPF does not broadcast the first multicast packet it receives. The protocol builds a source-rooted, shortest-path tree on demand when it receives the first multicast packet and then prunes the branches not associated with this group. Also, MOSPF does not allow for tunneling as DVMRP does. Multicast datagrams are sent in native mode and are not encapsulated (DVMRP uses IP-in-IP encapsulation for tunneling). A difference between OSPF and MOSPF is that MOSPF does not allow for equal-cost multipaths. There are tie-breaking rules that have been identified for paths that are found to be equal when calculating the shortest-path tree. One of these rules is that, given an equal-cost path to a destination, the router or LAN with the higher IP address will be chosen. The second tie-breaking rule is that a broadcast-oriented network is always chosen over WAN routers (point-to-point links). MOSPF Differences MOSPF differs from DVMRP and PIM: It does not broadcast the first multicast packet it receives Multicast is an integral part of the protocol. The protocol builds a source-rooted tree on-demand and then prunes branches. Multicast members are part of the link state database. Routes are computed like real routes and they are put into the forwarding cache. MOSPF does not allow for equal cost multipath: Tie-breaking algorithms have been put into place MOSPF routes should be the DR and BDR in any mixed (i.e., non-MOSPF) environments.

Space Diversity on a Mobile Platform. Lee (Ref. 8) discusses both vertically separated and horizontally separated antennas on a mobile unit. For the vertical case, 1.5l is recommended for the vertical separation case and 0.5l for the horizontal

One of the important roles of the entropy for discrete random variables is in the AEP, which states that for a sequence of i.i.d. random variables, p(X1 , X2 , . . . , Xn ) is close to 2 nH (X) with high probability. This enables us to de ne the typical set and characterize the behavior of typical sequences. We can do the same for a continuous random variable. Theorem 8.2.1 Let X1 , X2 , . . . , Xn be a sequence of random variables drawn i.i.d. according to the density f (x). Then 1 log f (X1 , X2 , . . . , Xn ) E[ log f (X)] = h(X) in probability. n (8.10) Proof: The proof follows directly from the weak law of large numbers. This leads to the following de nition of the typical set. De nition For > 0 and any n, we de ne the typical set A(n) with respect to f (x) as follows: 1 A(n) = (x1 , x2 , . . . , xn ) S n : log f (x1 , x2 , . . . , xn ) h(X) , n (8.11) n where f (x1 , x2 , . . . , xn ) = i=1 f (xi ). The properties of the typical set for continuous random variables parallel those for discrete random variables. The analog of the cardinality of the typical set for the discrete case is the volume of the typical set for continuous random variables. De nition The volume Vol(A) of a set A Rn is de ned as Vol(A) =

Illustrated TCP/IP by Matthew G. Naugle Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471196568 Pub Date: 11/01/98

ventral pathway in movement control thus leads to an increased reliance on allocentric information Particularly important in the context of the current discussion of attentional processes, the ventral /dorsal dichotomy seems to have many features in common with the explicit and implicit (motor) learning distinction outlined in the previous section In particular, both distinctions are associated with different degrees of conscious awareness and involvement of (working) memory This has led some (eg, van der Kamp, Savelsbergh, & Oudejans, 2003) to hypothesize that implicit learning may chiefly involve engagement of the dorsal visual pathway, whereas explicit learning may also engage the ventral visual pathway, especially early in skill learning There is some experimental evidence to support this contention Rossetti (1998), for example, reported evidence that concurrent explicit verbalization induced involvement of the ventral pathway.