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'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
Cataloged from PDF version of article.We study the compressive diffusion strategies over
distributed networks based on the diffusion implementation and
adaptive extraction of the information from the compressed diffusion
data. We demonstrate that one can achieve a comparable
performance to the full information exchange configurations,
even if the diffused information is compressed into a scalar or
a single bit, i.e., a tremendous reduction in the communication
load. To this end, we provide a complete performance analysis
for the compressive diffusion strategies. We analyze the transient,
the steady-state and the tracking performances of the configurations
in which the diffused data is compressed into a scalar
or a single-bit. We propose a new adaptive combination method
improving the convergence performance of the compressive diffusion
strategies further. In the new method, we introduce one
more freedom-of-dimension in the combination matrix and adapt
it by using the conventional mixture approach in order to enhance
the convergence performance for any possible combination rule
used for the full diffusion configuration. We demonstrate that our
theoretical analysis closely follow the ensemble averaged results
in our simulations. We provide numerical examples showing the
improved convergence performance with the new adaptive combination
method while tremendously reducing the communication
load
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