On the exponential convergence rate for a non-gradient Fokker-Planck equation in computational neuroscience

DOI10.1007/BF03377381zbMath1386.35402arXiv1603.07192OpenAlexW2963194440MaRDI QIDQ1691817

Minh-Binh Tran, Simona Mancini, José Antonio Carrillo

Publication date: 25 January 2018

Published in: Journal of Elliptic and Parabolic Equations (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.07192

zbMATH Keywords

exponential convergencenon-gradient Fokker-Planck equationPoincaré coefficient

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Parabolic equations and parabolic systems (35K99) Fokker-Planck equations (35Q84)

Cites Work

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• ON CONVEX SOBOLEV INEQUALITIES AND THE RATE OF CONVERGENCE TO EQUILIBRIUM FOR FOKKER-PLANCK TYPE EQUATIONS
• Differential equations and convergence almost everywhere in strongly monotone semiflows
• Entropy dissipation methods for degenerate parabolic problems and generalized Sobolev inequalities
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