96 research outputs found
Solvability of some classes of nonlinear first-order difference equations by invariants and generalized invariants
[[abstract]]We introduce notion of a generalized invariant for difference equations, which naturally generalizes notion of an invariant for the equations. Some motivations, basic examples and methods for application of invariants in the theory of solvability of difference equations are given. By using an invariant, as well as, a generalized invariant it is shown solvability of two classes of nonlinear first-order difference equations of interest, for nonnegative initial values and parameters appearing therein, considerably extending and explaining some problems in the literature. It is also explained how these classes of difference equations can be naturally obtained from some linear second-order difference equations with constant coefficients. [ABSTRACT FROM AUTHOR]
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Beta-Beta Bounds: Finite-Blocklength Analog of the Golden Formula
It is well known that the mutual information between two random variables can
be expressed as the difference of two relative entropies that depend on an
auxiliary distribution, a relation sometimes referred to as the golden formula.
This paper is concerned with a finite-blocklength extension of this relation.
This extension consists of two elements: 1) a finite-blocklength channel-coding
converse bound by Polyanskiy and Verd\'{u} (2014), which involves the ratio of
two Neyman-Pearson functions (beta-beta converse bound); and 2) a novel
beta-beta channel-coding achievability bound, expressed again as the ratio of
two Neyman-Pearson functions.
To demonstrate the usefulness of this finite-blocklength extension of the
golden formula, the beta-beta achievability and converse bounds are used to
obtain a finite-blocklength extension of Verd\'{u}'s (2002) wideband-slope
approximation. The proof parallels the derivation of the latter, with the
beta-beta bounds used in place of the golden formula.
The beta-beta (achievability) bound is also shown to be useful in cases where
the capacity-achieving output distribution is not a product distribution due
to, e.g., a cost constraint or structural constraints on the codebook, such as
orthogonality or constant composition. As an example, the bound is used to
characterize the channel dispersion of the additive exponential-noise channel
and to obtain a finite-blocklength achievability bound (the tightest to date)
for multiple-input multiple-output Rayleigh-fading channels with perfect
channel state information at the receiver.Comment: to appear in IEEE Transactions on Information Theor
Non-linear Log-Sobolev inequalities for the Potts semigroup and applications to reconstruction problems
Consider a Markov process with state space , which jumps continuously to
a new state chosen uniformly at random and regardless of the previous state.
The collection of transition kernels (indexed by time ) is the Potts
semigroup. Diaconis and Saloff-Coste computed the maximum of the ratio of the
relative entropy and the Dirichlet form obtaining the constant in
the -log-Sobolev inequality (-LSI). In this paper, we obtain the best
possible non-linear inequality relating entropy and the Dirichlet form (i.e.,
-NLSI, ). As an example, we show . The more precise NLSIs have been shown by Polyanskiy and Samorodnitsky to
imply various geometric and Fourier-analytic results.
Beyond the Potts semigroup, we also analyze Potts channels -- Markov
transition matrices constant on and off diagonal. (Potts
semigroup corresponds to a (ferromagnetic) subset of matrices with positive
second eigenvalue). By integrating the -NLSI we obtain the new strong data
processing inequality (SDPI), which in turn allows us to improve results on
reconstruction thresholds for Potts models on trees. A special case is the
problem of reconstructing color of the root of a -colored tree given
knowledge of colors of all the leaves. We show that to have a non-trivial
reconstruction probability the branching number of the tree should be at least
This extends previous
results (of Sly and Bhatnagar et al.) to general trees, and avoids the need for
any specialized arguments. Similarly, we improve the state-of-the-art on
reconstruction threshold for the stochastic block model with balanced
groups, for all . These improvements advocate information-theoretic
methods as a useful complement to the conventional techniques originating from
the statistical physics
Global Stability of a Rational Difference Equation
We consider the higher-order nonlinear difference equation +1=(+−)/(1++−),=0,1,… with the parameters, and the initial conditions −,…,0 are nonnegative real numbers. We investigate the periodic character, invariant intervals, and the global asymptotic stability of all positive solutions of the above-mentioned equation. In particular, our results solve the open problem introduced by Kulenović and Ladas in their monograph (see Kulenović and Ladas, 2002)
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