Osvaldo Rosso

Institituto Tecnológico de Buenos Aires (ITBA) · Departamento de Bioingeniería

The use of chaotic systems in electronics, such as Pseudo-Random Number Generators (PRNGs), is very appealing. Among them, continuous-time ones are used less because, in addition to having strong temporal correlations, they require further computations to obtain the discrete solutions. Here, the time step and discretization method selection are fir...

How the brain processes information from external stimuli in order to perceive the world and act on it is one of the greatest questions in neuroscience. To address this question, different time series analyses techniques have been employed to characterize the statistical properties of brain signals during cognitive tasks. Typically, response-specif...

The brain is a biophysical system subject to information flows that may be thought of as a many-body architecture with a spatiotemporal dynamics described by its neuronal structures. The oscillatory nature of brain activity allows these structures (nodes) to be described as a set of coupled oscillators forming a network where the node dynamics and...

The use of information measures for model selection in geophysical models with subgrid parameterizations is examined. Although the resolved dynamical equations of atmospheric or oceanic global numerical models are well established, the development and evaluation of parameterizations that represent subgrid-scale effects pose a big challenge. For cli...

To understand how single neurons process sensory information, it is necessary to develop suitable stochastic models to describe the response variability of the recorded spike trains. Spikes in a given neuron are produced by the synergistic action of sodium and potassium of the voltage-dependent channels that open or close the gates. Hodgkin and Hux...

Bandt and Pompe introduced Permutation Entropy in 2002 for Time Series where equal values, xt1 = xt2, t1 = t2, were neglected and only inequalities between the xt were considered. Since then, this measure has been modified and extended, in particular in cases when the amount of equal values in the series can not be neglected, (i.e. heart rate varia...

Financial global crisis has devastating impacts to economies since early XX century and continues to impose increasing collateral damages for governments, enterprises, and society in general. Up to now, all efforts to obtain efficient methods to predict these events have been disappointing. However, the quest for a robust estimator of the degree of...

A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attention and treatment. In this work, we carefully study the ef...

We have experimentally quantified the temporal structural diversity from the coordinate fluctuations of a laser beam propagating through isotropic optical turbulence. The main focus here is on the characterization of the long-range correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium...

In this contribution, a comparison between different permutation entropies as classifiers of electroencephalogram (EEG) records corresponding to normal and pre-ictal states is made. A discrete probability distribution function derived from symbolization techniques applied to the EEG signal is used to calculate the Tsallis entropy, Shannon Entropy,...

In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-...

This paper analyzes the informational efficiency of oil market during the last three decades, and examines changes in informational efficiency with major geopolitical events, such as terrorist attacks, financial crisis and other important events. The series under study is the daily prices of West Texas Intermediate (WTI) in USD/BBL, commonly used a...

Neurons tend to fire a spike when they are near a bifurcation from resting state to spiking activity. It is a delicate balance between noise, dynamic currents and initial condition what determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source of spike generation; moreover, the biophysics and...

The phenomenon of synchronization between two or more areas of the brain coupled asymmetrically is a relevant issue for understanding mechanisms and functions within the cerebral cortex. Anticipated synchronization (AS) refers to the situation in which the receiver system synchronizes to the future dynamics of the sender system while the intuitivel...

This paper analyses Libor interest rates for seven different maturities and referred to operations in British pounds, euros, Swiss francs and Japanese yen, during the period 2001–2015. The analysis is performed by means of two quantifiers derived from information theory: the permutation Shannon entropy and the permutation Fisher information measure...

A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a...

In this paper we use the ordinal patterns probabilities associated with fractional Brownian motions for estimating the Hurst exponent of artificially generated and experimentally measured data. Numerical analysis show a reliable estimation of this scaling parameter, even when data with low resolution are analysed. Robustness to observational noise...

This work proposes the use of Information Theory for the characterization of vehicles behavior through their velocities. Three public data sets were used: (i) Mobile Century data set collected on Highway I-880, near Union City, California; (ii) Borlänge GPS data set collected in the Swedish city of Borlänge; and (iii) Beijing taxicabs data set coll...

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 sl...

We revisit the Fisher-Shannon representation plane HxF, evaluated using the Bandt and Pompe recipe to assign a probability distribution to atime series. Several stochastic dynamical (noises with f^-k,k>0, power spectrum) and chaotic processes (27 chaoticmaps) are analyzed so as to illustrate the approach. Our mainachievement is uncovering the infor...

The aim of this letter is to introduce the permutation min-entropy as an improved symbolic tool for identifying the existence of hidden temporal correlations in time series. On the one hand, analytical results obtained for the fractional Brownian motion stochastic model theoretically support this hypothesis. On the other hand, the analysis of sever...

The characterization of the dynamics associated with electroencephalogram (EEG) signal combining an orthogonal discrete wavelet transform analysis with quantifiers originated from information theory is reviewed. In addition, an extension of this methodology based on multiresolution quantities, called wavelet leaders, is presented. In particular, th...

A crucial challenge in network theory is to study how robust a network is when facing failures or attacks. In this work, we propose a novel methodology to measure the topological resilience and robustness of a network based on Information Theory quantifiers. This measure can be used with any probability distribution able to represent the network's...

Wildlife monitoring through Sensors Networks is a new tool used by biologists to acquire information about animals and their habitat. • Machine learning techniques are often used for automatic sound classification. • Before classification, each call needs to be segmented into smaller units called syllables (preprocessing step). • The correct segmen...

EEGs reflect the electrical activity of the brain that can be considered chaotic and ruled by a nonlinear dynamics. Chickens exhibit a protracted period of maturation and this temporal separation of the synapse formation and maturation phases is analogous to human neural development, though the changes in chickens occur in weeks compared with years...

This paper presents and discusses the use of a new feature for PolSAR imagery: the Generalized Statistical Complexity. This measure is able to capture the disorder of the data by means of the entropy, as well as its departure from a reference distribution. The latter component is obtained by measuring a stochastic distance between two models: the $...

A recently proposed methodology called the Horizontal Visibility Graph (HVG) [Luque {\it et al.}, Phys. Rev. E., 80, 046103 (2009)] that constitutes a geometrical simplification of the well known Visibility Graph algorithm [Lacasa {\it et al.\/}, Proc. Natl. Sci. U.S.A. 105, 4972 (2008)], has been used to study the distinction between deterministic...

In this paper we study the evolution of the informational efficiency in its weak form for seventeen European sovereign bonds time series. We aim to assess the impact of two specific economic situations in the hypothetical random behavior of these time series: the establishment of a common currency and a wide and deep financial crisis. In order to e...

Complexity-entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy versus Jensen-Shannon complexity that has been introduced in nonlinear dynamics analysis to classify signals according to their degrees of randomness and complexity. In this study, we explore the applicability of CECP in hydrological studies by ana...

The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For this purpose we use a powerful statistical tool, re...

Wireless sensor networks are an important technology for making distributed autonomous measures in hostile or inaccessible environments. Among the challenges they pose, the way data travel among them is a relevant issue since their structure is quite dynamic. The operational topology of such devices can often be described by complex networks. In th...

When calculating the Bandt and Pompe ordinal pattern distribution from given time series at depth D, some of the D! patterns might not appear. This could be a pure finite size effect (missing patterns) or due to dynamical properties of the observed system (forbidden patterns). For pure noise, no forbidden patterns occur, contrary to deterministic c...

We consider a network of cortical spiking neurons with axonal conduction delays and spike timing dependent plasticity (STDP), which is representative of a cortical column or hypercolumn. Each neuron fires following a Hodgkin-Huxley like dynamics and it is interconnected randomly to another neurons. In this work we use a permutation entropy approach...

By appealing to a long list of different nonlinear maps we review the characterization of time series arising from chaotic maps. The main tool for this characterization is the permutation Bandt-Pompe probability distribution function. We focus attention on both local and global characteristics of the components of this probability distribution func...

We present an application of wavelet-based Information Theory quantifiers (Relative Wavelet Energy, Normalized Total Wavelet Entropy, Wavelet MPR-Statistical Complexity and Entropy-Complexity plane) on red blood cells membrane viscoelasticity characterization. These quantifiers exhibit important localization advantages provided by the Wavelet Theor...

In this paper we study the evolution of the informational efficiency in its weak form for 17 European Union sovereign bonds time series. We aim to assess the impact of two specific economic situations in the random behavior of time series: the establishment of a common currency and a wide and deep financial crisis. In order to assess the informatio...

This chapter deals with the use of the Statistical Complexity Measure, as defined by López Ruiz, Mancini and Calbet [Phys. Lett. A 209 (1995) 321–326] and modified by Rosso and coworkers [P. W. Lamberti, M. T. Martín, A. Plastino, O. A. Rosso; Physica A 334 (2004) 119–131] to characterize pseudo random number generators (PRNG's) obtained from chaot...

We deal here with the issue of determinism versus randomness in time series (TS), with the goal of identifying their relative importance in a given TS. To this end we extend (i) the use of ordinal patterns based probability distribution functions associated to a TS [C. Bandt and B. Pompe, Phys. Rev. Lett. 88, 174102 (2002)] and (ii) the so-called A...

The temperature profile during the process of cooling is an important parameter in the design and description of any protocol for cryopreservation. Rapid and ultra-rapid cooling procedures, in which liquid nitrogen (LN2) is used as cooling agent, require special equipment and methods in order to record and analyze the thermal history of the sample...

A new methodology based on information theory is used to explore the evolution of the surface air temperature climate network over the Tropical Pacific region. Topological changes over the period 1948–2009 are investigated using windows of one year duration. Alternating states of lower/higher efficiency in information transfer are consistently capt...

In this paper we introduce a multiscale symbolic information-theory approach for discriminating nonlinear deterministic and stochastic dynamics from time series associated with complex systems. More precisely, we show that the multiscale complexity-entropy causality plane is a useful representation space to identify the range of scales at which det...

The existence of memory in financial time series has been extensively studied for several stock markets around the world by means of different approaches. However, fixed income markets, i.e. those where corporate and sovereign bonds are traded, have been much less studied. We believe that, given the relevance of these markets, not only from the inv...

Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculatin...

A new generalized Statistical Complexity Measure (SCM) was proposed by Rosso et al in 2010. It is a functional that captures the notions of order/disorder and of distance to an equilibrium distribution. The former is computed by a measure of entropy, while the latter depends on the definition of a stochastic divergence. When the scene is illuminate...

At issue here is the distinction between noise and chaos. They are different phenomena but sometimes produce results that resemble each other. From a numerical viewpoint, in particular, subtle differences that exist between them are often difficult to discern. We present here a conceptual scheme, based on Information Theory, that successfully disti...

The quantum-classical limit together with the associated onset of chaos is employed here in order to illustrate the importance of a proper choice of distance in probability space if one wishes to describe dynamical properties from the information theory viewpoint.

We analyze the statistical complexity measure vs. entropy plane-representation of sampled chaotic attractors as a function of the sampling period ττ and show that, if the Bandt and Pompe procedure is used to assign a probability distribution function (PDF) to the pertinent time series, the statistical complexity measure (SCM) attains a definite max...

By recourse to the concept of Statistical Complexity we study here the classical-quantum transition in a special system that represents the matter-field interaction. Our work considers two distinct disequilibrium forms based on Euclidean norm and Jensen-Shannon divergence, on the one hand, and analyzes things, on the other one, by using two differe...

Spread-spectrum techniques for improving Electromagnetic Compatibilities are investigated. This requires generating Constant Envelope Wideband signals. We produce them via chaotic maps that yield pseudo random time series, used afterwards to modulate sinusoidal waves in frequency. How to assess a maps's suitability for such task is also discussed.

A methodology to analyze dynamical changes in dynamic climate systems based on complex networks and Information Theory quantifiers is discussed. In particular, the square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, is used to quantify states in the network evolution process by means of th...

Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii) distances in probability-space. In consequence, SCMs provide a simultaneous quantification of the randomness and the correlational structures present in the system under study. We address in this review important topics underlying the SCM structure,...

Analysis of the Tsallis qq-triplet for the variability of El Niño Southern Oscillation (ENSO) index during the Holocene epoch (last 11,000 years) is presented. Three periods are analyzed, 0–7000, 7000–9700, 9700–11,000 years before the present. During the first and the third periods, the qq-index values have the expected usual relations between the...

The time evolution of the output of a semiconductor laser subject to delayed optical feedback can exhibit high-dimensional 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...

We investigate the classical limit of the dynamics of a semiclassical system that represents the interaction between matter and a given field. The concept of Fisher Information measure (F) on using as a quantifier of the process, we find that it adequately describes the transition, detecting the most salient details of the changeover. Used in conju...

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, i) the "causal" entropy-complexity plane [Rosso et al. Phys. Rev. Lett. 99 (2007) 154102] and ii) the estimation of the de...

We analyze the statistical complexity vs. entropy plane-representation of sampled chaotic attractors as a function of the sampling period {\tau}. It is shown that if the Bandt and Pompe procedure is used to assign a probability distribution function (PDF) to the pertinent time series, the statistical complexity measure (SCM) attains a definite maxi...

It is widely known that commodity markets are not totally efficient. Long-range dependence is present, and thus the celebrated Brownian motion of prices can be considered only as a first approximation. In this work we analyzed the predictability in commodity markets by using a novel approach derived from Information Theory. The complexity–entropy c...

We analyze the intrinsic time scales of the chaotic dynamics of a semiconductor laser subject to optical feedback by estimating quantifiers derived from a permutation information approach. Based on numerically and experimentally obtained times series, we find that permutation entropy and permutation statistical complexity allow the extraction of im...

This study investigates the effects produced by an increased concentration of glucose in a suspending medium on the erythrocytes Information Theory quantifiers. Erythrocytes, which were obtained from eight healthy volunteers, were washed and incubated in vitro with glucose solutions at different concentrations. The measured Wavelet-based Informatio...

Statistical complexity measures are used to quantify the degree of complexity of the delayed logistic map, with linear and nonlinear feedback. We employ two methods for calculating the complexity measures, one with the 'histogram-based' probability distribution function and the other one with ordinal patterns. We show that these methods provide com...

The Bandt–Pompe (BP) prescription for building up probability densities [C. Bandt, B. Pompe, Permutation entropy: a natural complexity measure for time series, Phys. Rev. Lett. 88 (2002) 174102] constituted a significant advance in the treatment of time-series. However, as we show here, ambiguities arise in applying the BP technique with reference...

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analy...

This study explores temporal changes in the dynamics of the Holocene ENSO proxy record of the Laguna Pallcacocha sedimentary data using two entropy quantifiers. In particular, we analyze the possible connections between changes in entropy and epochs of rapid climate change (RCC). Our results indicate that the dynamics of the ENSO proxy record durin...

We highlight the potentiality of a special Information Theory (IT) approach in order to unravel the intricacies of nonlinear dynamics, the methodology being illustrated with reference to the logistic map. A rather surprising dynamic feature→plane-topography map becomes available.

In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These quantifiers show clear extrema when the embedding del...

We present an application of wavelet-based Information Theory quantifiers (Normalized Total Shannon Entropy, MPR-Statistical Complexity and Entropy-Complexity plane) on red blood cells membrane viscoelasticity characterization. These quantifiers exhibit important localization advantages provided by the Wavelet Theory. The present approach produces...

Low-frequency fluctuations (LFFs) represent a dynamical instability that occurs in semiconductor lasers when they are operated near the lasing threshold and subject to moderate optical feedback. LFFs consist of sudden power dropouts followed by gradual, stepwise recoveries. We analyze experimental time series of intensity dropouts and quantify the...

Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the “ordinal patterns” [C. Bandt, B. Pompe, Phys. Rev. Lett. 88 (2002) 174102]. In particular, new insight has been obtained considering the emergence of the so-called “forbidden ordinal patterns” [J....

The complexity-entropy causality plane has been recently introduced as a powerful tool for discriminating Gaussian from non-Gaussian process and different degrees of correlations [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102]. We propose to use this representat...

Supplementary Data 1. (4.10 MB XLS)

Supplementary Data 2. (1.26 MB XLS)