956 resultados para SYNCHRONIZATION OF CHAOS


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In this paper, we consider non-ideal excitation devices such as DC motors with restrictenergy output capacity. When such motors are attached to structures which needexcitation power levels similar to the source power capacity, jump phenomena and theincrease in power required near resonance characterize the Sommerfeld Effect, actingas a sort of an energy sink. One of the problems often faced by designers of suchstructures is how to drive the system through resonance and avoid this energy sink.Our basic structural model is a simple portal frame driven by a num-ideal powersource-(NIPF). We also investigate the absorption of resonant vibrations (nonlinearand chaotic) by means of a nonlinear sub-structure known as a Nonlinear Energy Sink(NES). An energy exchange process between the NIPF and NES in the passagethrough resonance is investigated, as well the suppression of chaos.

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In this work, a method that synchronizes two video sequences is proposed. Unlike previous methods, which require the existence of correspondences between features tracked in the two sequences, and/or that the cameras are static or jointly moving, the proposed approach does not impose any of these constraints. It works when the cameras move independently, even if different features are tracked in the two sequences. The assumptions underlying the proposed strategy are that the intrinsic parameters of the cameras are known and that two rigid objects, with independent motions on the scene, are visible in both sequences. The relative motion between these objects is used as clue for the synchronization. The extrinsic parameters of the cameras are assumed to be unknown. A new synchronization algorithm for static or jointly moving cameras that see (possibly) different parts of a common rigidly moving object is also proposed. Proof-of-concept experiments that illustrate the performance of these methods are presented, as well as a comparison with a state-of-the-art approach.

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We here present a synchronization of the NGRIP, GRIP, and GISP2 ice cores based mainly on volcanic events over the period 14.9-32.45 ka b2k (before AD 2000), corresponding to Marine Isotope Stage 2 (MIS 2) and the end of MIS 3. The matching provides a basis for applying the recent NGRIP-based Greenland Ice Core Chronology 2005 (GICC05) time scale to the GRIP and GISP2 ice cores, thereby making it possible to compare the synchronized palaeoclimate profiles of the cores in detail and to identify relative accumulation differences between the cores. Based on the matching, a period of anomalous high accumulation rates in the GISP2 ice core is detected within the period 16.5-18.3 ka b2k. The d18O and [Ca2+] profiles of the three cores are presented on the common GICC05 time scale and generally show excellent agreement across the stadial-interstadial transitions and across the two characteristic dust events in Greenland Stadial 3. However, large differences between the d18O and [Ca2+] profiles of the three cores are seen in the same period as the 7-9% increase in the GISP2 accumulation rate. We conclude that changes of the atmospheric circulation are likely to have occurred in this period, altering the spatial gradients in Greenland and resulting in larger variations between the records.

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We here present a synchronization of the NGRIP, GRIP, and GISP2 ice cores based mainly on volcanic events over the period 14.9-32.45 ka b2k (before AD 2000), corresponding to Marine Isotope Stage 2 (MIS 2) and the end of MIS 3. The matching provides a basis for applying the recent NGRIP-based Greenland Ice Core Chronology 2005 (GICC05) time scale to the GRIP and GISP2 ice cores, thereby making it possible to compare the synchronized palaeoclimate profiles of the cores in detail and to identify relative accumulation differences between the cores. Based on the matching, a period of anomalous high accumulation rates in the GISP2 ice core is detected within the period 16.5-18.3 ka b2k. The d18O and [Ca2+] profiles of the three cores are presented on the common GICC05 time scale and generally show excellent agreement across the stadial-interstadial transitions and across the two characteristic dust events in Greenland Stadial 3. However, large differences between the d18O and [Ca2+] profiles of the three cores are seen in the same period as the 7-9% increase in the GISP2 accumulation rate. We conclude that changes of the atmospheric circulation are likely to have occurred in this period, altering the spatial gradients in Greenland and resulting in larger variations between the records.

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The DEEP site sediment sequence obtained during the ICDP SCOPSCO project at Lake Ohrid was dated using tephrostratigraphic information, cyclostratigraphy, and orbital tuning through the marine isotope stages (MIS) 15-1. Although this approach is suitable for the generation of a general chronological framework of the long succession, it is insufficient to resolve more detailed palaeoclimatological questions, such as leads and lags of climate events between marine and terrestrial records or between different regions. Here, we demonstrate how the use of different tie points can affect cyclostratigraphy and orbital tuning for the period between ca. 140 and 70 ka and how the results can be correlated with directly/indirectly radiometrically dated Mediterranean marine and continental proxy records. The alternative age model presented here shows consistent differences with that initially proposed by Francke et al. (2015) for the same interval, in particular at the level of the MIS6-5e transition. According to this new age model, different proxies from the DEEP site sediment record support an increase of temperatures between glacial to interglacial conditions, which is almost synchronous with a rapid increase in sea surface temperature observed in the western Mediterranean. The results show how a detailed study of independent chronological tie points is important to align different records and to highlight asynchronisms of climate events. Moreover, Francke et al. (2016) have incorporated the new chronology proposed for tephra OH-DP-0499 in the final DEEP age model. This has reduced substantially the chronological discrepancies between the DEEP site age model and the model proposed here for the last glacial-interglacial transition.

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We analyze the properties of networks obtained from the trajectories of unimodal maps at the transi- tion to chaos via the horizontal visibility (HV) algorithm. We find that the network degrees fluctuate at all scales with amplitude that increases as the size of the network grows, and can be described by a spectrum of graph-theoretical generalized Lyapunov exponents. We further define an entropy growth rate that describes the amount of information created along paths in network space, and find that such en- tropy growth rate coincides with the spectrum of generalized graph-theoretical exponents, constituting a set of Pesin-like identities for the network.

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We examine the connectivity fluctuations across networks obtained when the horizontal visibility (HV) algorithm is used on trajectories generated by nonlinear circle maps at the quasiperiodic transition to chaos. The resultant HV graph is highly anomalous as the degrees fluctuate at all scales with amplitude that increases with the size of the network. We determine families of Pesin-like identities between entropy growth rates and generalized graph-theoretical Lyapunov exponents. An irrational winding number with pure periodic continued fraction characterizes each family. We illustrate our results for the so-called golden, silver, and bronze numbers

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In subjects suffering from early onset strabismus, signals conveyed by the two eyes are not perceived simultaneously but in alternation. We exploited this phenomenon of interocular suppression to investigate the neuronal correlate of binocular rivalry in primary visual cortex of awake strabismic cats. Monocularly presented stimuli that were readily perceived by the animal evoked synchronized discharges with an oscillatory patterning in the γ-frequency range. Upon dichoptic stimulation, neurons responding to the stimulus that continued to be perceived increased the synchronicity and the regularity of their oscillatory patterning while the reverse was true for neurons responding to the stimulus that was no longer perceived. These differential changes were not associated with modifications of discharge rate, suggesting that at early stages of visual processing the degree of synchronicity rather than the amplitude of responses determines which signals are perceived and control behavioral responses.

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Deterministic chaos has been implicated in numerous natural and man-made complex phenomena ranging from quantum to astronomical scales and in disciplines as diverse as meteorology, physiology, ecology, and economics. However, the lack of a definitive test of chaos vs. random noise in experimental time series has led to considerable controversy in many fields. Here we propose a numerical titration procedure as a simple “litmus test” for highly sensitive, specific, and robust detection of chaos in short noisy data without the need for intensive surrogate data testing. We show that the controlled addition of white or colored noise to a signal with a preexisting noise floor results in a titration index that: (i) faithfully tracks the onset of deterministic chaos in all standard bifurcation routes to chaos; and (ii) gives a relative measure of chaos intensity. Such reliable detection and quantification of chaos under severe conditions of relatively low signal-to-noise ratio is of great interest, as it may open potential practical ways of identifying, forecasting, and controlling complex behaviors in a wide variety of physical, biomedical, and socioeconomic systems.

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The collective behavior of interconnected spiking nerve cells is investigated. It is shown that a variety of model systems exhibit the same short-time behavior and rapidly converge to (approximately) periodic firing patterns with locally synchronized action potentials. The dynamics of one model can be described by a downhill motion on an abstract energy landscape. Since an energy landscape makes it possible to understand and program computation done by an attractor network, the results will extend our understanding of collective computation from models based on a firing-rate description to biologically more realistic systems with integrate-and-fire neurons.