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10 l.

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The learning algorithms presented in the previous section, although of practical value, have been derived in a heuristic or intuitive way. In this section, we derive the e cient natural gradient learning algorithm in a mathematically rigorous way [1365]. Let us assume without loss of generality that the number of outputs is equal to the number of sensors and the matrix D IRm m is nonsingular. From the linear output equation (11.4), we have x(k) = D 1 (y(k) C (k)). (11.41) Substituting (11.41) into (11.18), we obtain d y = (d C d D D 1 C) + d D D 1 y + C d . (11.42)

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Figure 33-7

(9.87)

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all the queues, otherwise a proper decision cannot be taken We therefore restrict ourselves to a simple case, with only two queues; we furthermore assume that the switch-over delays are equal to zero Under these assumptions, this polling model can be seen as a model of a traffic multiplexer for two classes of traffic Lee and Sengupta recently proposed such a polling mechanism as a flexible priority mechanism to be used in high-speed networking switches [178] They proposed their socalled threshold priority policy (TPP) as a priority mechanism that gives priority to one traffic class over another, only when really needed In the following, we will assume that the two traffic classes are a video or real-time class (rt) and a data or nonreal-time class (nrt) In the TPP, two buffers are used for the two traffic classes A predetermined threshold L is associated with the real-time buffer.

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When the queue length in the real-time buffer is less than or equal to L, the server alternates between the two buffers transmitting one cell from each buffer (as long as a queue is not empty) On the other hand, when the queue length in the real-time buffer exceeds L, the server continues to serve the real-time buffer until its queue length is reduced to L The value of the threshold L gives the degree of preferential treatment of the real-time traffic When L = 0, real-time traffic is given an absolute non-preemptive priority When L = 00, both traffic classes are served alternatingly when not empty, ie, the server acts as a l-limited cyclic server By selecting L between these two extremes, one may provide an adequate quality of service to both real-time and nonreal-time traffic In Figure 16.

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