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    Distributed functional scalar quantization simplified

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    Date Issued
    2013-07
    Publisher Version
    10.1109/tsp.2013.2259483
    Author(s)
    Sun, John Z.
    Misra, Vinith
    Goyal, Vivek K.
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    Permanent Link
    https://hdl.handle.net/2144/42542
    Version
    First author draft
    Citation (published version)
    John Z Sun, Vinith Misra, Vivek K Goyal. 2013. "Distributed Functional Scalar Quantization Simplified." IEEE Transactions on Signal Processing, Volume 61, Issue 14, pp. 3495 - 3508. https://doi.org/10.1109/tsp.2013.2259483
    Abstract
    Distributed functional scalar quantization (DFSQ) theory provides optimality conditions and predicts performance of data acquisition systems in which a computation on acquired data is desired. We address two limitations of previous works: prohibitively expensive decoder design and a restriction to source distributions with bounded support. We show that a much simpler decoder has equivalent asymptotic performance to the conditional expectation estimator studied previously, thus reducing decoder design complexity. The simpler decoder features decoupled communication and computation blocks. Moreover, we extend the DFSQ framework with the simpler decoder to source distributions with unbounded support. Finally, through simulation results, we demonstrate that performance at moderate coding rates is well predicted by the asymptotic analysis, and we give new insight on the rate of convergence.
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