FRINK Linked Data Fragments server

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• W2978465332 abstract "Consider the following communication scenario. An $n$-dimensional source with memory is observed by $K$ isolated encoders via parallel channels, who causally compress their observations to transmit to the decoder via noiseless rate-constrained links. At each time instant, the decoder receives $K$ new codewords from the observers, combines them with the past received codewords, and produces a minimum-distortion estimate of the latest block of $n$ source symbols. This scenario extends the classical one-shot CEO problem to multiple rounds of communication with communicators maintaining the memory of the past. We extend the Berger-Tung inner and outer bounds to the scenario with inter-block memory, showing that the minimum asymptotically (as $n to infty$) achievable sum rate required to achieve a target distortion is bounded by minimal directed mutual information problems. For the Gauss-Markov source observed via $K$ parallel AWGN channels, we show that the inner bound is tight and solve the corresponding minimal directed mutual information problem, thereby establishing the minimum asymptotically achievable sum rate. Finally, we explicitly bound the rate loss due to a lack of communication among the observers; that bound is attained with equality in the case of identical observation channels. The general coding theorem is proved via a new nonasymptotic bound that uses stochastic likelihood coders and whose asymptotic analysis yields an extension of the Berger-Tung inner bound to the causal setting. The analysis of the Gaussian case is facilitated by reversing the channels of the observers." @default.
• W2978465332 created "2019-10-10" @default.
• W2978465332 creator A5001633086 @default.
• W2978465332 creator A5002430773 @default.
• W2978465332 date "2019-10-06" @default.
• W2978465332 modified "2023-09-27" @default.
• W2978465332 title "Fundamental limits of distributed tracking" @default.
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• W2978465332 hasPublicationYear "2019" @default.
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