On maximum likelihood identification of spatially-varying parameters in stochastic parabolic systems

Article type: Research Article

Authors: Aihara, Shin Ichi^a

Affiliations: [a] Department of Management and Systems Science, The Science University of Tokyo, Suwa College, 5000-1,Toyohira, Chino Nagano, 391-02, Japan. Tel.: +81 266 731201; Fax: +81 266 731230; E-mail: [email protected]

Abstract: The maximum likelihood estimation (M.L.E.) for spatially-varying parameters in stochastic parabolic systems is studied. The main result is to show the consistency property of the M.L.E. for unknown parameters by using the method of sieves, i.e., first the admissible class of unknown parameters is projected into a finite-dimensional space and next the convergence of the derived finite-dimensional M.L.E. to the infinite-dimensional M.L.E. is justified under some conditions. Finally numerical examples are presented.

DOI: 10.3233/JAE-2000-170

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 11, no. 1, pp. 3-18, 2000