Journal ArticleDOI
Self-organized criticality: An explanation of the 1/ f noise
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TLDR
It is shown that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point, and flicker noise, or 1/f noise, can be identified with the dynamics of the critical state.Abstract:
We show that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point. Flicker noise, or 1/f noise, can be identified with the dynamics of the critical state. This picture also yields insight into the origin of fractal objects.read more
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Journal ArticleDOI
Pattern formation outside of equilibrium
Michael Cross,P. C. Hohenberg +1 more
TL;DR: A comprehensive review of spatiotemporal pattern formation in systems driven away from equilibrium is presented in this article, with emphasis on comparisons between theory and quantitative experiments, and a classification of patterns in terms of the characteristic wave vector q 0 and frequency ω 0 of the instability.
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Neuronal Oscillations in Cortical Networks
György Buzsáki,Andreas Draguhn +1 more
TL;DR: Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information.
Journal ArticleDOI
Power laws, Pareto distributions and Zipf's law
TL;DR: Some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them are reviewed.
Book
The Mechanics of Earthquakes and Faulting
TL;DR: The connection between faults and the seismicity generated is governed by the rate and state dependent friction laws -producing distinctive seismic styles of faulting and a gamut of earthquake phenomena including aftershocks, afterslip, earthquake triggering, and slow slip events.
Journal ArticleDOI
Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series
TL;DR: A new method--detrended fluctuation analysis (DFA)--for quantifying this correlation property in non-stationary physiological time series is described and application of this technique shows evidence for a crossover phenomenon associated with a change in short and long-range scaling exponents.