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ASYMPTOTIC HOMOGENIZATION IN A PARABOLIC SEMILINEAR PROBLEM WITH PERIODIC COEFFICIENTS AND INTEGRABLE INITIAL DATA
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作者 Rogerio Luiz Quintino de OLIVEIRA JUNIOR 《Acta Mathematica Scientia》 SCIE CSCD 2013年第5期1275-1292,共18页
In this paper, we study the large time behavior of solutions of the parabolic semilinear equation δtu-div(a(x)△↓u) = -|u|^αu in (0,∞) × R^N, where α 〉 0 is constant and a∈ Cb^1(R^N) is a symmetr... In this paper, we study the large time behavior of solutions of the parabolic semilinear equation δtu-div(a(x)△↓u) = -|u|^αu in (0,∞) × R^N, where α 〉 0 is constant and a∈ Cb^1(R^N) is a symmetric periodic matrix satisfying some ellipticity assumptions.Considering an integrable initial data u0 and α ∈ (2/N, 3/N), we prove that the large time behavior of solutions is given by the solution U(t, x) of the homogenized linear problem δtU-div(a^h△↓U)=0,U(0) = C, where a^h is the homogenized matrix of a(x), C is a positive constant and δ is the Dirac measure at 0. 展开更多
关键词 HOMOGENIZATION similinear parabolic equation integrable initial data matrix with periodic coefficient large time behavior
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Time Series of Random Macro-price and Application
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作者 耿显民 《Chinese Quarterly Journal of Mathematics》 CSCD 北大核心 2008年第1期144-155,共12页
This paper tries to utilize the methods of stochastic analysis and matrix analysis to research the existential problem of price series. By using the means of time series analysis, the input-output, Markov processes an... This paper tries to utilize the methods of stochastic analysis and matrix analysis to research the existential problem of price series. By using the means of time series analysis, the input-output, Markov processes and the modern matrix analysis, the limiting problem of price balance and vibration in stochastic economic environment has been researched, and surprising conclusions obtained are as following: the probability that the economic collapse time is equal ∞ is 0. 展开更多
关键词 input-output coefficient matrix economic collapse time maximum eigne value random perturbation Markov process
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