Browsing by Subject "CEO problem"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Differential entropy of the conditional expectation under additive gaussian voise
    (Institute of Electrical and Electronics Engineers, 2022) Atalik, Arda; Köse, Alper; Gastpar, Michael
    The conditional mean is a fundamental and important quantity whose applications include the theories of estimation and rate-distortion. It is also notoriously difficult to work with. This paper establishes novel bounds on the differential entropy of the conditional mean in the case of finite-variance input signals and additive Gaussian noise. The main result is a new lower bound in terms of the differential entropies of the input signal and the noisy observation. The main results are also extended to the vector Gaussian channel and to the natural exponential family. Various other properties such as upper bounds, asymptotics, Taylor series expansion, and connection to Fisher Information are obtained. Two applications of the lower bound in the remote-source coding and CEO problem are discussed.
  • Thumbnail Image
    ItemOpen Access
    The Price of Distributed: Rate Loss in the CEO Problem
    (Institute of Electrical and Electronics Engineers (IEEE), 2022-04-14) Atalik, Arda; Köse, A.; Gastpar, M.
    In the distributed remote (CEO) source coding problem, many separate encoders observe independently noisy copies of an underlying source. The rate loss is the difference between the rate required in this distributed setting and the rate that would be required in a setting where the encoders can fully cooperate. In this sense, the rate loss characterizes the price of distributed processing. We survey and extend the known results on the rate loss in various settings, with a particular emphasis on the case where the noise in the observations is Gaussian, but the underlying source is general.