Jin-liang Yan

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The cellular neural network (CNN) method is applied to solve the Pennes bioheat transfer equation, and its feasibility is demonstrated. Numerical solutions were obtained for a cellular neural network for a two-dimensional steady-state temperature field obtained from focused and unfocused ultrasound heat sources. Transient-state temperature fields were also(More)
fung durch L = L allein wfirde zu LixV307 fiihren. Zwischen den beiden Extremen ist eine Reihe der homologen Strukturen LixV6.O15n-m denkbar, wobei n und m die Anzahl der Baueinheiten bzw. der Doppelverknfipfungen (L = L) in einer Elementarzelle darstellen. Die ebengenannten homologen Strukturen sind alle monoklin, die m6glichen Raumgruppen sind P21/m,(More)
In this paper, two-grid methods for characteristic finite volume element solutions are presented for the semilinear Sobolev equation. The method is based on the methods of characteristics, two-grid method and the finite volume element method. The nonsymmetric and nonlinear iterations are only executed on the coarse grid (with grid size H). And the finegrid(More)
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