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Rank these systems in order of decreasing entropy.
Rank these systems in order of decreasing entropy.





rank these systems in order of decreasing entropy.

A., “ Analysis of ischaemic crisis using the informational causal entropy-complexity plane,” Chaos 28, 075309 (2018). O., Cymberknop, L., Armentano, R., and Rosso, O. The obtained results enhance the functional role of gamma oscillations in the formation of neural representations of perception during visuomotor action and imagery activities. Their aim is to characterize the complexity of the EEG rhythmic oscillation bands when the subjects perform a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. provide a quantification of the degree of complexity of different brain rhythmic oscillations of the EEG signals, by means of information theoretical approach. A., and Montani, F., “ Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks,” Chaos 28, 075513 (2018). The EEG is the product of synchronized activity of the brain, and variations in EEG oscillation patterns reflect the underlying changes in neuronal synchrony.

rank these systems in order of decreasing entropy.

In this way, the results of this work allow one to transduce song like activity during sleep into synthetic sounds.Įlectroencephalography (EEG) signals depict the electrical activity that takes place at the surface of the brain and provide an important tool for understanding a variety of cognitive processes. This is particularly interesting since it has been shown that male zebra finches ( Taeniopygia guttata) exhibit spontaneous song-like activity in the syringealis ventralis muscle during the night. In awake animals, this work reports a quantification of the similarity between synthetic songs (generated with the song production model driven by syringealis ventralis activity) and the actual birdsong (produced as the muscle activity was being recorded). B., “ Gating related activity in a syringeal muscle allows the reconstruction of zebra finches songs,” Chaos 28, 075517 (2018)., it is shown that the information carried out by the syringealis ventralis muscle can also be used to determine whether the songbird is phonating at a given time. F., Bush, A., Amador, A., Goller, F., and Mindlin, G. Recently, a biophysically inspired dynamical system has allowed researchers to carry out explicitly this translation of electrical activity into frequency modulation of birdsong. In particular, the syringealis ventralis muscle has been reported to be involved in the control of the tension of the vibrating labia and thus to affect the frequency modulation of the generated sound. The next article deals with birdsong production, which requires delicate and fast activation of several muscles in order to control the configuration of the syrinx (the avian vocal organ) and the respiratory system. This is an important result because the number of iterations is related to the time needed to reach equilibrium and consequently to the energy consumption in spectrum allocation systems.

rank these systems in order of decreasing entropy.

Finally, classic equilibrium, which implies low expectations, is reached in fewer amounts of iterations. On the other hand, the highest Nash equilibrium is reached when some players have high expectation, and all the players apply the quantum strategy Q. When all players have low expectation level, quantum improves and complexity could not be necessary because the theoretically highest Nash equilibrium cannot be obtained. The level of expectation of the players is defined as a decision parameter. This is a toy model of users of a communication network competing for scarce spectrum resources. propose a quantum minority game that exploits the properties of quantum superposition and entanglement at the same time. M., “ Evolutionary quantum minority game: a wireless network application,” Chaos 28, 075506 (2018). In the first contribution, Zabaleta and Arizmendi (2018) 20.







Rank these systems in order of decreasing entropy.