本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2009
摘要
Extremization of the Boltzmann-Gibbs (BG) 熵 S-BG = - k integral dx p(x) lnp(x) under appropriate norm and width constraints yields the Gaussian distribution p(G)(x) proportional to e(-beta x2). Also, the basic solutions of the standard Fokker-Planck (FP) equation (related to the Langevin equation with additive noise), as well as the Central Limit Theorem 吸引子s, are Gaussians. The simplest 隨機 model with such features is N -> 8 independent binary random variables, as first proved by de Moivre and Laplace. What happens for strongly correlated random variables? Such correlations are often present in physical situations as e. g. systems with long range interactions or memory. Frequently q-Gaussians, p(q)(x) proportional to 1-(1-q)beta x(2) [p(1)(x) = p(G)(x)] become observed. This is
※ 此為已發表論文，全文需透過期刊付費取得