Titlebook: Information Processing in Sensor Networks; Second International Feng Zhao,Leonidas Guibas Conference proceedings 2003 Springer-Verlag Berli

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Bounds on Achievable Rates for General Multi-terminal Networks with Practical Constraints multi-hop network and the relay channel with cheap nodes is presented. In both of these cases, the bounds are tight enough to provide converses for the coding theorems [.], and thus their respective capacities are derived.

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Source-Channel Communication in Sensor Networksd be to approach our condition for optimal performance as closely as possible. This is supported by examples for which our coding paradigm significantly outperforms the traditional separation-based coding paradigm. In particular, for a Gaussian example considered in this paper, the distortion of the

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On Rate-Constrained Estimation in Unreliable Sensor Networksptimality property: ...When the network has clusters of collaborating sensors should clusters compress their raw measurements or should they first try to estimate the source from their measurements and compress the estimates instead. For some interesting cases, we show that there is no loss of perfo

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Hypothesis Testing over Factorizations for Data Associationons, and show the resulting algorithm’s ability to determine correspondence in uncertain conditions through a series of synthetic examples. We then describe an extension of this technique to multi-signal association which can be used to determine correspondence while avoiding the computationally pro

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