In stochastic systems with non-diagonal noise and switching environments, mutual information includes irreducible static and dynamic interference terms that prevent simple decomposition.
Risken, Fokker-planck equation, inThe Fokker-Planck equation: methods of solution and applications(Springer
4 Pith papers cite this work. Polarity classification is still indexing.
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Derives a closed non-Markovian diffusion equation generalizing the Fokker-Planck equation for non-stationary Gaussian velocity processes via a hierarchy of Wick contractions.
A superstatistical analytical model reproduces multimodal frequency distributions, heavy-tailed fluctuations, and double-exponential autocorrelations in real grid data from two countries while also fitting spatial phase-angle statistics.
Noise-driven switching between expression basins in frustrated genes, locked by slow epigenetic feedback, produces robust input-dependent differentiation with logarithmic time dependence on noise strength.
citing papers explorer
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Emergence of information interference in stochastic systems with non-diagonal noise and switching environments
In stochastic systems with non-diagonal noise and switching environments, mutual information includes irreducible static and dynamic interference terms that prevent simple decomposition.
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The diffusion equation for non-Markovian Gaussian stochastic processes
Derives a closed non-Markovian diffusion equation generalizing the Fokker-Planck equation for non-stationary Gaussian velocity processes via a hierarchy of Wick contractions.
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Understanding the complexity of frequency and phase angle fluctuations in power grids
A superstatistical analytical model reproduces multimodal frequency distributions, heavy-tailed fluctuations, and double-exponential autocorrelations in real grid data from two countries while also fitting spatial phase-angle statistics.
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Noise-Driven Differentiation via Gene Frustration and Epigenetic Fixation
Noise-driven switching between expression basins in frustrated genes, locked by slow epigenetic feedback, produces robust input-dependent differentiation with logarithmic time dependence on noise strength.