Hydrometeorological time series like river discharge or precipitation often show signatures of fr... more Hydrometeorological time series like river discharge or precipitation often show signatures of fractal noise or chaotic, nonlinear dynamics. Lakes as the “terminal sink” of water collected in its catchment should reflect those signatures at least in part. For lakes nonlinear techniques were applied by Sangoyomi et al. (1996) to show that variations in the volume of the Great Salt Lake, a large, closed basin lake, may be described as a low-dimensional nonlinear dynamical system. There also exists a direct link between regional as well as global climatic fluctuations and eco-hydrological time series of lakes, e.g. zooplankton abundance and lake surface temperature (Straile et al., 2003). Thus lake levels and plankton abundance which are forced by external meteorological and hydrological processes might show similar dynamical behaviour. Here we analyze eco-hydrological time series of Lake Constance using nonlinear techniques to test for the possible existence of low-dimensional nonlinear dynamics. Apart from nonlinear dynamics of eco-hydrological time series characterized by external forcing, such time series can show chaotic behaviour due to their “internal” dynamics. Resource competition models of phytoplankton can generate oscillations and chaos when species compete for three or more resources (Huisman and Weissing, 1999). Examples of such nonlinear dynamics are shown.
Eye tracking is an emerging technology with a wide spectrum of applications, including non-invasi... more Eye tracking is an emerging technology with a wide spectrum of applications, including non-invasive neurocognitive diagnosis. An advantage of the use of eye trackers is in the improved assessment of indirect latent information about several aspects of the subjects’ neurophysiology. The path to uncover and take advantage of the meaning and implications of this information, however, is still in its very early stages. In this work, we apply ordinal patterns transition networks as a means to identify subjects with dyslexia in simple text reading experiments. We registered the tracking signal of the eye movements of several subjects (either normal or with diagnosed dyslexia). The evolution of the left-to-right movement over time was analyzed using ordinal patterns, and the transitions between patterns were analyzed and characterized. The relative frequencies of these transitions were used as feature descriptors, with which a classifier was trained. The classifier is able to distinguish typically developed vs dyslexic subjects with almost 100% accuracy only analyzing the relative frequency of the eye movement transition from one particular permutation pattern (plain left to right) to four other patterns including itself. This characterization helps understand differences in the underlying cognitive behavior of these two groups of subjects and also paves the way to several other potentially fruitful analyses applied to other neurocognitive conditions and tests.
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020
The brain is a biophysical system subject to information flows that may be thought of as a many-b... more 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 that of the network topology can be studied. Quantifying its dynamics at various scales is an issue that claims to be explored for several brain activities, e.g., activity at rest. The resting-state (RS) associates the underlying brain dynamics of healthy subjects that are not actively compromised with sensory or cognitive processes. Studying its dynamics is highly non-trivial but opens the door to understand the general principles of brain functioning, as well as to contrast a passive null condition vs the dynamics of pathologies or non-resting activities. Here, we hypothesize about how the spatiotemporal dynamics of cortical fluctuations...
International journal of applied mathematics and statistics, Feb 2, 2012
Spread-spectrum techniques for improving Electromagnetic Compatibilities are investigated. This r... more 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.
Hydrometeorological time series like river discharge or precipitation often show signatures of fr... more Hydrometeorological time series like river discharge or precipitation often show signatures of fractal noise or chaotic, nonlinear dynamics. Lakes as the “terminal sink” of water collected in its catchment should reflect those signatures at least in part. For lakes nonlinear techniques were applied by Sangoyomi et al. (1996) to show that variations in the volume of the Great Salt Lake, a large, closed basin lake, may be described as a low-dimensional nonlinear dynamical system. There also exists a direct link between regional as well as global climatic fluctuations and eco-hydrological time series of lakes, e.g. zooplankton abundance and lake surface temperature (Straile et al., 2003). Thus lake levels and plankton abundance which are forced by external meteorological and hydrological processes might show similar dynamical behaviour. Here we analyze eco-hydrological time series of Lake Constance using nonlinear techniques to test for the possible existence of low-dimensional nonlinear dynamics. Apart from nonlinear dynamics of eco-hydrological time series characterized by external forcing, such time series can show chaotic behaviour due to their “internal” dynamics. Resource competition models of phytoplankton can generate oscillations and chaos when species compete for three or more resources (Huisman and Weissing, 1999). Examples of such nonlinear dynamics are shown.
Eye tracking is an emerging technology with a wide spectrum of applications, including non-invasi... more Eye tracking is an emerging technology with a wide spectrum of applications, including non-invasive neurocognitive diagnosis. An advantage of the use of eye trackers is in the improved assessment of indirect latent information about several aspects of the subjects’ neurophysiology. The path to uncover and take advantage of the meaning and implications of this information, however, is still in its very early stages. In this work, we apply ordinal patterns transition networks as a means to identify subjects with dyslexia in simple text reading experiments. We registered the tracking signal of the eye movements of several subjects (either normal or with diagnosed dyslexia). The evolution of the left-to-right movement over time was analyzed using ordinal patterns, and the transitions between patterns were analyzed and characterized. The relative frequencies of these transitions were used as feature descriptors, with which a classifier was trained. The classifier is able to distinguish typically developed vs dyslexic subjects with almost 100% accuracy only analyzing the relative frequency of the eye movement transition from one particular permutation pattern (plain left to right) to four other patterns including itself. This characterization helps understand differences in the underlying cognitive behavior of these two groups of subjects and also paves the way to several other potentially fruitful analyses applied to other neurocognitive conditions and tests.
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020
The brain is a biophysical system subject to information flows that may be thought of as a many-b... more 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 that of the network topology can be studied. Quantifying its dynamics at various scales is an issue that claims to be explored for several brain activities, e.g., activity at rest. The resting-state (RS) associates the underlying brain dynamics of healthy subjects that are not actively compromised with sensory or cognitive processes. Studying its dynamics is highly non-trivial but opens the door to understand the general principles of brain functioning, as well as to contrast a passive null condition vs the dynamics of pathologies or non-resting activities. Here, we hypothesize about how the spatiotemporal dynamics of cortical fluctuations...
International journal of applied mathematics and statistics, Feb 2, 2012
Spread-spectrum techniques for improving Electromagnetic Compatibilities are investigated. This r... more 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.
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Papers by Osvaldo Anibal Rosso