3,058 research outputs found
On the average uncertainty for systems with nonlinear coupling
The increased uncertainty and complexity of nonlinear systems have motivated
investigators to consider generalized approaches to defining an entropy
function. New insights are achieved by defining the average uncertainty in the
probability domain as a transformation of entropy functions. The Shannon
entropy when transformed to the probability domain is the weighted geometric
mean of the probabilities. For the exponential and Gaussian distributions, we
show that the weighted geometric mean of the distribution is equal to the
density of the distribution at the location plus the scale, i.e. at the width
of the distribution. The average uncertainty is generalized via the weighted
generalized mean, in which the moment is a function of the nonlinear source.
Both the Renyi and Tsallis entropies transform to this definition of the
generalized average uncertainty in the probability domain. For the generalized
Pareto and Student's t-distributions, which are the maximum entropy
distributions for these generalized entropies, the appropriate weighted
generalized mean also equals the density of the distribution at the location
plus scale. A coupled entropy function is proposed, which is equal to the
normalized Tsallis entropy divided by one plus the coupling.Comment: 24 pages, including 4 figures and 1 tabl
Noise Induced Phenomena in the Dynamics of Two Competing Species
Noise through its interaction with the nonlinearity of the living systems can
give rise to counter-intuitive phenomena. In this paper we shortly review noise
induced effects in different ecosystems, in which two populations compete for
the same resources. We also present new results on spatial patterns of two
populations, while modeling real distributions of anchovies and sardines. The
transient dynamics of these ecosystems are analyzed through generalized
Lotka-Volterra equations in the presence of multiplicative noise, which models
the interaction between the species and the environment. We find noise induced
phenomena such as quasi-deterministic oscillations, stochastic resonance, noise
delayed extinction, and noise induced pattern formation. In addition, our
theoretical results are validated with experimental findings. Specifically the
results, obtained by a coupled map lattice model, well reproduce the spatial
distributions of anchovies and sardines, observed in a marine ecosystem.
Moreover, the experimental dynamical behavior of two competing bacterial
populations in a meat product and the probability distribution at long times of
one of them are well reproduced by a stochastic microbial predictive model.Comment: 23 pages, 8 figures; to be published in Math. Model. Nat. Phenom.
(2016
Noise in ecosystems: a short review
Noise, through its interaction with the nonlinearity of the living systems,
can give rise to counter-intuitive phenomena such as stochastic resonance,
noise-delayed extinction, temporal oscillations, and spatial patterns. In this
paper we briefly review the noise-induced effects in three different
ecosystems: (i) two competing species; (ii) three interacting species, one
predator and two preys, and (iii) N-interacting species. The transient dynamics
of these ecosystems are analyzed through generalized Lotka-Volterra equations
in the presence of multiplicative noise, which models the interaction between
the species and the environment. The interaction parameter between the species
is random in cases (i) and (iii), and a periodical function, which accounts for
the environmental temperature, in case (ii). We find noise-induced phenomena
such as quasi-deterministic oscillations, stochastic resonance, noise-delayed
extinction, and noise-induced pattern formation with nonmonotonic behaviors of
patterns areas and of the density correlation as a function of the
multiplicative noise intensity. The asymptotic behavior of the time average of
the \emph{} population when the ecosystem is composed of a great number
of interacting species is obtained and the effect of the noise on the
asymptotic probability distributions of the populations is discussed.Comment: 27 pages, 16 figures. Accepted for publication in Mathematical
Biosciences and Engineerin
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