广义神经传播方程一个新的超收敛估计及外推  

A New Superconvergence Analysis and Extrapolation for Generalized Neure Conductive Equations

作　　者：吴志勤[1] 王芬玲[1] 石东洋[2] 

机构地区：[1]许昌学院数学与统计学院,河南许昌461000 [2]郑州大学数学系,河南郑州450052

出　　处：《数学的实践与认识》2011年第15期234-240,共7页Mathematics in Practice and Theory

基　　金：国家自然科学基金(10671184;10971203);河南省教育厅(2010A110018)

摘　　要：主要目的是研究双线性元对一类非线性广义神经传播方程的逼近.并利用积分恒等式及插值后处理技巧,导出H^1模及L^2模意义下的超逼近性和超收敛结果.同时,通过构造一个新的外推格式,得到了与线性问题精度完全相同的外推结果,进一步拓宽了双线性元的应用范围.The main purpose of this paper is to study the bilinear element approximation for a class of nonlinear generalized neure conductive equations approximation. The superclose property and the superconvergence of H1 and the L2 norms are given by means of integral identities and the interpolation post-processing techniques. At the same time, extrapolating results with the same accuracy as the linear problem are obtained through a newly structured extrapolation form, and the applications of bilinear element are extended.

关 键 词：广义神经传播方程 超收敛 双线性元 外推 

分 类 号：O241.82[理学—计算数学]