2,857 research outputs found
Successive Wyner-Ziv Coding Scheme and its Application to the Quadratic Gaussian CEO Problem
We introduce a distributed source coding scheme called successive Wyner-Ziv
coding. We show that any point in the rate region of the quadratic Gaussian CEO
problem can be achieved via the successive Wyner-Ziv coding. The concept of
successive refinement in the single source coding is generalized to the
distributed source coding scenario, which we refer to as distributed successive
refinement. For the quadratic Gaussian CEO problem, we establish a necessary
and sufficient condition for distributed successive refinement, where the
successive Wyner-Ziv coding scheme plays an important role.Comment: 28 pages, submitted to the IEEE Transactions on Information Theor
The CEO Problem with Secrecy Constraints
We study a lossy source coding problem with secrecy constraints in which a
remote information source should be transmitted to a single destination via
multiple agents in the presence of a passive eavesdropper. The agents observe
noisy versions of the source and independently encode and transmit their
observations to the destination via noiseless rate-limited links. The
destination should estimate the remote source based on the information received
from the agents within a certain mean distortion threshold. The eavesdropper,
with access to side information correlated to the source, is able to listen in
on one of the links from the agents to the destination in order to obtain as
much information as possible about the source. This problem can be viewed as
the so-called CEO problem with additional secrecy constraints. We establish
inner and outer bounds on the rate-distortion-equivocation region of this
problem. We also obtain the region in special cases where the bounds are tight.
Furthermore, we study the quadratic Gaussian case and provide the optimal
rate-distortion-equivocation region when the eavesdropper has no side
information and an achievable region for a more general setup with side
information at the eavesdropper.Comment: Accepted for publication in IEEE Transactions on Information
Forensics and Security, 17 pages, 4 figure
Mean Estimation from One-Bit Measurements
We consider the problem of estimating the mean of a symmetric log-concave
distribution under the constraint that only a single bit per sample from this
distribution is available to the estimator. We study the mean squared error as
a function of the sample size (and hence the number of bits). We consider three
settings: first, a centralized setting, where an encoder may release bits
given a sample of size , and for which there is no asymptotic penalty for
quantization; second, an adaptive setting in which each bit is a function of
the current observation and previously recorded bits, where we show that the
optimal relative efficiency compared to the sample mean is precisely the
efficiency of the median; lastly, we show that in a distributed setting where
each bit is only a function of a local sample, no estimator can achieve optimal
efficiency uniformly over the parameter space. We additionally complement our
results in the adaptive setting by showing that \emph{one} round of adaptivity
is sufficient to achieve optimal mean-square error
Diffusion Kinetics in Radiation Chemistry. II. One-Radical-One-Solute Model; Calculations
The general diffusionākinetic equations are applied to a oneāradicalāoneāsolute model of the radiolysis of dilute aqueous solutions. The validity of the prescribed diffusion approximation is examined. Results of calculations of the effect on the molecular and radical yields of the following parameters are given: solute concentration, solute depletion, shape of initial radical distribution, radical density, diffusion coefficients, and rate constants. Conditions under which a straight track of equal and equidistant spherical spurs can be replaced by either isolated spherical spurs or an axially homogeneous cylindrical track are examined
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