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Let C(Gs) = f (Gs)gT (Gs) I. Condition (A.1) is necessary to allow the separation solution G = I to be an equilibrium point of the algorithm, i.e., E{C(G s)} = 0. The next step is to study the asymptotic stability of the algorithm at this point. For this purpose, we will study the behavior of the Ordinary Di erential Equation (ODE) associated with the algorithm at the separation solution [96, 97]. Let us de ne the mean eld of the algorithm as M (G) = E{C(Gs)G} and an arbitrary small matrix perturbation of the global transfer matrix at the separation solution G . Then, M (I + ) = E{C(s + s)(I + )} = E{C(s + s)} + O( ), (A.15)



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Essential Windows CE Application Programming by Robert Burdick Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471327476 Pub Date: 03/01/99





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Researchers in multiagent systems may be predominantly concerned with engineering systems, but t h s is by no means their only concern. As with its stable mate AI, the issues addressed by the multiagent systems field have profound implications for our understanding of ourselves. A1 has been largely focused on the issues of intelligence in individuals. But surely a large part of what makes us unique as a species is our social ability. Not only can we communicate with one another in high-level languages, we can cooperate, coordinate, and negotiate with one another. Whle many other species have social ability of a lund - ants and other social insects being perhaps the best-known examples - no other species even begins to approach us in the sophistication of our social ability. In multiagent systems, we address ourselves to such questions as follow. How can cooperation emerge in societies of self-interested agents What sorts of common languages can agents use to communicate their beliefs and aspirations, both to people and to other agents How can self-interested agents recognize when their beliefs, goals, or actions conflict, and how can they reach agreements with one another on matters of self-interest, without resorting to conflict How can autonomous agents coordinate their activities so as to cooperatively achieve goals While these questions are all addressed in part by other disciplines (notably economics and the social sciences), what makes the multiagent systems field unique and distinct is that it emphasizes that the agents in question are computational, information processing entities.

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Although in our analysis we will always assume that the resistors are linear and arc thus described by a straigh t-line characteristic that passes throug h the orig in, it is impo rtant !.hat readers reali ze th at some very useful and practical elements do ex ist that ex hibit a nonlinea r resis tance charac teristi c; that is, the vohage-<:urrent relation ship is not a straight line.

The trifecta of scripting languages beginning with P ends with ython, and is completed by Libgmail, the Python bindings for Gmail access.

The simulated performance of a 512-subcarrier 16QAM PSAM modem in the presence of a constant timing error of T = lOT, in an AWGN channel is depicted in Figure 13.9 for both ideal low-pass and for simple linear interpolation. Following Equation 13.18, the maximum acceptable pilot subcarrier distance required for resolving a normalized FIT-window misalignment of m = r / T s = 10 is A p = N/20 = 512/20 = 25.6, requiring at least 20 pilot subcarriers equidistantly spaced in the OFDM symbol. We can see in both graphs of Figure 13.9 that the bit error rate is 0.5 for both schemes, if less than 20 pilot subcarriers are employed in the OFDM symbol. For pilot numbers above the required minimum of 20, however, the performance of the ideal low-pass interpolated PSAM scheme does not vary with the number of pilots employed, while the linearly interpolated PSAM scheme needs higher numbers of pilot subcarriers in order to achieve a similar performance. The continuous lines in the graphs show the BER for a coherently detected 16QAM OFDM modem in the absence of timing errors, while utilizing no PSAM. Observe in the figure that there is a BER penalty for PSAM in a narrow-band AWGN channel, since the pilots are affected by noise, which is interpreted by the PSAM schemes as a channel induced fluctuation, which has tobe compensated.

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