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- W3204139654 abstract "Distributions maximizing the (S_q) power-law entropies are observed in the behavior of complex systems arising in a remarkably wide range of disciplines, including neuroscience. One known effective description of processes leading to these maximum entropy distributions is provided by nonlinear, power-law Fokker–Planck equations. In this work, we explore an evolution equation of this type, associated with the celebrated Cohen–Grossberg model of neural network dynamics. We prove that the stationary distributions of this evolution equation have the (S_q) maximum entropy form. These distributions are q-exponentials with an argument proportional to the energy function (also known as Liapunov function) corresponding to the Cohen–Grossberg dynamics. The nonlinear Fokker–Planck equation investigated here also obeys an H-theorem in terms of a free energy-like quantity that is a linear combination of the energy function and of an (S_q) entropy. These findings may help to understand the origin of the (S_q) maximum entropy distributions observed in brain dynamics." @default.
- W3204139654 created "2021-10-11" @default.
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- W3204139654 date "2021-01-01" @default.
- W3204139654 modified "2023-10-16" @default.
- W3204139654 title "Nonlinear Fokker–Planck Approach to the Cohen–Grossberg Model" @default.
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- W3204139654 doi "https://doi.org/10.1007/978-981-16-0317-4_7" @default.
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