Download Information and Control in Networks by Massimo Franceschetti, Paolo Minero (auth.), Giacomo Como, PDF

By Massimo Franceschetti, Paolo Minero (auth.), Giacomo Como, Bo Bernhardsson, Anders Rantzer (eds.)

Information and regulate in Networks demonstrates the way procedure dynamics and data flows intertwine as they evolve, and the valuable function performed by means of info within the regulate of advanced networked structures. it's a milestone at the highway to that convergence from usually autonomous improvement of keep watch over thought and data concept which has emerged strongly within the final fifteen years, and is now a truly energetic study box. as well as efforts up to speed and knowledge concept, the textual content is witness to robust learn in such varied fields as machine technological know-how, arithmetic, and facts. facets which are given expert remedy include:

· data-rate theorems;

· computation and keep watch over over conversation networks;

· decentralized stochastic control;

· Gaussian networks and Gaussian–Markov random fields; and

· routability in details networks.

Information and keep an eye on in Networks collects contributions from world-leading researchers within the sector who got here jointly for the Lund heart for regulate of complicated Engineering platforms Workshop in details and keep an eye on in Networks from 17th–19th October 2012; the workshop being the centrepiece of a five-week-long concentration interval at the related subject. A resource of fascinating cross-fertilization and new principles for large destiny study, this quantity should be of significant curiosity to any researcher or graduate scholar attracted to the interplay of keep watch over and data theory.

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Information and Control in Networks

Details and keep an eye on in Networks demonstrates the way method dynamics and data flows intertwine as they evolve, and the primary position performed through info within the keep an eye on of advanced networked platforms. it's a milestone at the highway to that convergence from regularly autonomous improvement of keep an eye on concept and knowledge thought which has emerged strongly within the final fifteen years, and is now a truly lively study box.

Extra resources for Information and Control in Networks

Example text

M 20 M. Franceschetti and P. 38) because the difference between the two estimates at time k − d is amplified by λ at each iteration due to the expansion of the state process. 39) d=0 where Pd,k = P {Mˆ 0|k = M0 , . . , Mˆ k−d−1|k = Mk−d−1 , Mˆ k−d|k = Mk−d }, denotes the probability that the index of the first wrong estimate at time k is k − d, d = 0, 1, . . , k. 3) is satisfied, while the second denotes the mean-square error between the estimator x¯k available at the encoder and the estimator xˆk available at the decoder, and is bounded provided Pd,k decays fast enough as d grows.

Consider the special case of a rate process that randomly switches between two different states, state r¯1 and r¯2 , and where the transition probabilities from r¯1 to r¯2 and from r¯2 to r¯1 are denoted by p and q, respectively. In this case, it is possible to relate the spectral radius of H to its determinant det(H ) and its trace tr(H ). 1 reduces to |λ|2 tr(H ) + 2 tr(H )2 − 4 det(H ) < 1. 47) (d) Erasure Channel. Another special case that has been studied in the literature is the case of an erasure channel, which is further specialization of the two-state Markov process described above in the case where r¯1 = 0, r¯2 = r¯ .

Similarly, most of the existing works assume a perfect channel from the controller to the actuator. The case where both the sensor–controller and the controller–actuator channels are noisy was studied in [73], which provides conditions for second moment stability using Markov stability theory. In general, however, it is not known when the criteria summarized in this chapter continue to hold 34 M. Franceschetti and P. Minero after replacing the relevant notion of capacity with the capacity of the bottleneck channel.

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