147 research outputs found
Noise versus chaos in a causal Fisher-Shannon plane
We revisit the Fisher-Shannon representation plane , evaluated using the Bandt and Pompe recipe to assign a
probability distribution to a time series. Several stochastic dynamical (noises
with , , power spectrum) and chaotic processes (27 chaotic
maps) are analyzed so as to illustrate the approach. Our main achievement is
uncovering the informational properties of the planar location.Comment: 6 pages, 1 figure. arXiv admin note: text overlap with
arXiv:1401.213
Efficiency characterization of a large neuronal network: a causal information approach
When inhibitory neurons constitute about 40% of neurons they could have an
important antinociceptive role, as they would easily regulate the level of
activity of other neurons. We consider a simple network of cortical spiking
neurons with axonal conduction delays and spike timing dependent plasticity,
representative of a cortical column or hypercolumn with large proportion of
inhibitory neurons. Each neuron fires following a Hodgkin-Huxley like dynamics
and it is interconnected randomly to other neurons. The network dynamics is
investigated estimating Bandt and Pompe probability distribution function
associated to the interspike intervals and taking different degrees of
inter-connectivity across neurons. More specifically we take into account the
fine temporal ``structures'' of the complex neuronal signals not just by using
the probability distributions associated to the inter spike intervals, but
instead considering much more subtle measures accounting for their causal
information: the Shannon permutation entropy, Fisher permutation information
and permutation statistical complexity. This allows us to investigate how the
information of the system might saturate to a finite value as the degree of
inter-connectivity across neurons grows, inferring the emergent dynamical
properties of the system.Comment: 26 pages, 3 Figures; Physica A, in pres
Classification and Verification of Online Handwritten Signatures with Time Causal Information Theory Quantifiers
We present a new approach for online handwritten signature classification and
verification based on descriptors stemming from Information Theory. The
proposal uses the Shannon Entropy, the Statistical Complexity, and the Fisher
Information evaluated over the Bandt and Pompe symbolization of the horizontal
and vertical coordinates of signatures. These six features are easy and fast to
compute, and they are the input to an One-Class Support Vector Machine
classifier. The results produced surpass state-of-the-art techniques that
employ higher-dimensional feature spaces which often require specialized
software and hardware. We assess the consistency of our proposal with respect
to the size of the training sample, and we also use it to classify the
signatures into meaningful groups.Comment: Submitted to PLOS On
Libor at crossroads: stochastic switching detection using information theory quantifiers
This paper studies the 28 time series of Libor rates, classified in seven
maturities and four currencies), during the last 14 years. The analysis was
performed using a novel technique in financial economics: the
Complexity-Entropy Causality Plane. This planar representation allows the
discrimination of different stochastic and chaotic regimes. Using a temporal
analysis based on moving windows, this paper unveals an abnormal movement of
Libor time series arround the period of the 2007 financial crisis. This
alteration in the stochastic dynamics of Libor is contemporary of what press
called "Libor scandal", i.e. the manipulation of interest rates carried out by
several prime banks. We argue that our methodology is suitable as a market
watch mechanism, as it makes visible the temporal redution in informational
efficiency of the market.Comment: 17 pages, 9 figures. arXiv admin note: text overlap with
arXiv:1508.04748, arXiv:1509.0021
The (in)visible hand in the Libor market: an Information Theory approach
This paper analyzes several interest rates time series from the United
Kingdom during the period 1999 to 2014. The analysis is carried out using a
pioneering statistical tool in the financial literature: the complexity-entropy
causality plane. This representation is able to classify different stochastic
and chaotic regimes in time series. We use sliding temporal windows to assess
changes in the intrinsic stochastic dynamics of the time series. Anomalous
behavior in the Libor is detected, especially around the time of the last
financial crisis, that could be consistent with data manipulation.Comment: PACS 89.65.Gh Econophysics; 74.40.De noise and chao
A permutation Information Theory tour through different interest rate maturities: the Libor case
This paper analyzes Libor interest rates for seven different maturities and
referred to operations in British Pounds, Euro, Swiss Francs and Japanese Yen,
during the period years 2001 to 2015. The analysis is performed by means of two
quantifiers derived from Information Theory: the permutation Shannon entropy
and the permutation Fisher information measure. An anomalous behavior in the
Libor is detected in all currencies except Euro during the years 2006--2012.
The stochastic switch is more severe in 1, 2 and 3 months maturities. Given the
special mechanism of Libor setting, we conjecture that the behavior could have
been produced by the manipulation that was uncovered by financial authorities.
We argue that our methodology is pertinent as a market overseeing instrument.Comment: arXiv admin note: text overlap with arXiv:1304.039
Characterizing the Hyperchaotic Dynamics of a Semiconductor Laser Subject to Optical Feedback Via Permutation Entropy
The time evolution of the output of a semiconductor
laser subject to delayed optical feedback can exhibit highdimensional chaotic fluctuations. In this contribution, our aim
is to quantify the degree of unpredictability of this hyperchaotic
time evolution. To that end, we estimate permutation entropy, a
novel information-theory-derived quantifier particularly robust
in a noisy environment. The permutation entropy is defined as
a functional of a symbolic probability distribution, evaluated
using the Bandt-Pompe recipe to assign a probability distribution
function to the time series generated by the chaotic system.
This measure quantifies the diversity of orderings present in the
associated time series. In order to evaluate the performance of
this novel quantifier, we compare with the results obtained by
using a more standard chaos quantifier, namely the KolmogorovSinai entropy. Here, we present numerical results showing that
the permutation entropy, evaluated at specific time-scales involved in the chaotic regime of the semiconductor laser subject
to optical feedback, give valuable information about the degree
of unpredictability of the chaotic laser dynamics. The influence
of additive observational noise on the proposed tool is also
investigated.L.Z. and O.A.R. were supported by
Consejo Nacional de Investigaciones Cient´ıficas y T´ecnicas
(CONICET), Argentina. O.A.R. is PVE fellowship, CAPES,
Brazil. Part of this work was funded by MEC (Spain),
MICINN (Spain) and FEDER under Projects TEC2009-14101
(DeCoDicA) and FIS2007-60327 (FISICOS), and by the EC
Project PHOCUS Grant 240763.Peer reviewe
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