By Frank Ohrtman
Written for community engineers, this ebook offers the knowledge for company implementations. It provides info on designing and construction WiFi networks of scale, and covers just about all instant environments. it's also motives of regulatory, protection, and financial concerns, and case reviews to demonstrate implementation suggestion.
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Adaptive Optimization of CSMA/CA MAC Protocols 35  V. Krishnamurthy and G. G. Yin. 2002. Recursive algorithms for estimation of hidden Markov models and autoregressive models with Markov regime. IEEE Trans. Inf. Theory 48:458–76.  J. J. Ford and J. B. Moore. 1998. Adaptive estimation of HMM transition probabilities. IEEE Trans. Signal Process. 46:1374–85.  F. LeGland and L. Mevel. 1997. Recursive estimation in hidden Markov models. In Proceedings of the Conference on Decision and Control, vol.
9. ∀k, update the sufficient statistics Tt(k) = Tt(xt(k), yt). 10. 26). 11. end for A more accurate estimate of A can easily be obtained by updating the sufficient statistics and estimating A before the selection step. However, this would induce a heavier computational load. 2 Approximate MAP Estimator For HMM with known parameters, the Viterbi algorithm provides a recursive solution to get the best state sequence estimation in terms of the maximum a posteriori (MAP) . When the parameters are unknown, the most common procedure is to use an EM algorithm, which only converges to some local maximum of the a posteriori density, but above all, it is a batch procedure and thus cannot be used in our setting.