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INTERACTING TIME-FRACTIONAL AND Δν PDES SYSTEMS VIA BROWNIAN-TIME AND INVERSE-STABLE-LÉVY-TIME BROWNIAN SHEETS

机译:通过布朗时间和逆稳定莱维时间布朗表交互作用时间分数和ΔνPDES系统

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摘要

Lately, many phenomena in both applied and abstract mathematics and related disciplines have been expressed in terms of high order and fractional PDEs. Recently, Allouba introduced the Brownian-time Brownian sheet (BTBS) and connected it to a new system of fourth order interacting PDEs. The interaction in this multiparameter BTBS-PDEs connection is novel, leads to an intimately-connected linear system variant of the celebrated Kuramoto–Sivashinsky PDE, and is not shared with its one-time-parameter counterpart. It also means that these PDEs systems are to be solved for a family of functions, a feature exhibited in well known fluids dynamics models. On the other hand, the memory-preserving interaction between the PDE solution and the initial data is common to both the single- and the multi-parameter Brownian-time PDEs. Here, we introduce a new — even in the one-parameter case — proof that combines stochastic analysis with analysis and fractional calculus to simultaneously link BTBS to a new system of temporally half-derivative interacting PDEs as well as to the fourth-order system proved earlier and differently by Allouba. We then introduce a general class of random fields we call inverse-stable-Lévy-time Brownian sheets (ISLTBSs), and we link them to β-fractional-time-derivative systems of interacting PDEs for 0 < β < 1. When β = 1/ν, ν ∈ {2, 3, …}, our proof also connects an ISLTBS to a system of memory-preserving ν-Laplacian interacting PDEs. Memory is expressed via a sum of temporally-scaled k-Laplacians of the initial data, k = 1, …, ν - 1. Using a Fourier–Laplace-transform-fractional-calculus approach, we give a conditional equivalence result that gives a necessary and sufficient condition for the equivalence between the fractional and the high order systems. In the one-parameter case this condition automatically holds.
机译:最近,应用数学和抽象数学以及相关学科中的许多现象都以高阶和分数PDE的形式表达。最近,Allouba推出了布朗时布朗表(BTBS),并将其连接到新的四阶相互作用PDE系统。这种多参数BTBS-PDE连接中的相互作用是新颖的,导致了著名的Kuramoto-Sivashinsky PDE的紧密连接的线性系统变体,并且没有与它的一次性参数共享。这也意味着这些PDE系统需要解决一系列功能,这是众所周知的流体动力学模型所具有的功能。另一方面,PDE解决方案与初始数据之间的内存保留交互作用对于单参数和多参数布朗时间PDE都是相同的。在这里,我们介绍了一个新的(即使在单参数情况下)证明,它将随机分析与分析和分数演算相结合,以将BTBS同时链接到一个新的时间半导数相互作用PDE系统以及四阶系统。较早而不同的是阿洛巴。然后,我们引入一类一般的随机字段,我们称其为逆稳定-Lévy-time布朗表(ISLTBS),并将它们链接到0 <β<1时相互作用的PDE的β分数时间导数系统。 1 /ν,ν∈{2,3,…},我们的证明也将ISLTBS连接到保存内存的ν-拉普拉斯相互作用PDE的系统。内存通过初始数据的时间尺度k-拉普拉斯和的总和表示,k = 1,…,ν-1。使用傅立叶-拉普拉斯变换分数分数微积分方法,我们给出了条件等价结果,该结果给出了分数系统与高阶系统之间相等的必要和充分条件。在单参数情况下,此条件自动成立。

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