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1.
[0,1], - H .

This paper was written during the author's scholarship at the State University of Odessa in the USSR.  相似文献   

2.
( ) . .

Dedicated to Professor K. Tandori on his seventieth birthday

This research was supported in part by Grant # K41 100 of the Joint Fund of the Government of Ukraine and the International Science Foundation.  相似文献   

3.
{p mn } - 00>0, (1, 1) (1.1) (1.2). {s mn } J p - ( bJ p -lims mn =), (1.3) 0<x,y<1 p s (, )/p(x, y) x, y 1-. {r mn } - , (1.5) 0<, <1. N rp - , (1.6). , bJ p -lims mn = bJ q -lim(N rps) mn =. J p - . , .  相似文献   

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— [0,1] ,E — - e=1 [0,1]. I — E =1, E=L 2 x e =xL 2 x E.

This work was prepared when the second author was a visiting professor of the CNR at the University of Firenze. He was supported by the Soros International Fund.  相似文献   

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, a n f n (x) . .  相似文献   

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. . — . — —.

Herrn Professor Dr. Frank Terpe zum 60. Geburtstag gewidmet  相似文献   

14.
[3] , >0 n a n , . , . . , .

This research was partially supported by the Hungarian National Foundation for Scientific Research under Grant #234.  相似文献   

15.
In this note we consider the Gross-Pitaevskii equation i t ++(1–2)=0, where is a complex-valued function defined on N×, and study the following 2-parameters family of solitary waves: (x, t)=e it v(x 1ct, x), where and x denotes the vector of the last N–1 variables in N . We prove that every distribution solution , of the considered form, satisfies the following universal (and sharp) L -bound:
This bound has two consequences. The first one is that is smooth and the second one is that a solution 0 exists, if and only if . We also prove a non-existence result for some solitary waves having finite energy. Some more general nonlinear Schrödinger equations are considered in the third and last section. The proof of our theorems is based on previous results of the author ([7]) concerning the Ginzburg-Landau system of equations in N .Received May 31, 2002 Published online February 7, 2003  相似文献   

16.
n- (n1) fL p ([–, ] n ),=1 = (L C) . , , f([–, ] n ).  相似文献   

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(0; 0, 1) , {x k <x k * <x k+1} k=1 n–1 {x k k=1 n }., I, , n (x)=P n (, ) (x)–n- , =, n3 . , x 0=+1 x n+1= –1. II .

To the memory of Paul Erds

The research was supported by the Hungarian National Foundation for Scientific Research under Grant # T 914 244.  相似文献   

19.
(C, ). , . 0<<1. 1) - ( k ), k =a k , (C, ), . 2) , , (C, ) ; k = =¦a k ¦.  相似文献   

20.
Let X 1, , X n (n > p) be a random sample from multivariate normal distribution N p (, ), where R p and is a positive definite matrix, both and being unknown. We consider the problem of estimating the precision matrix –1. In this paper it is shown that for the entropy loss, the best lower-triangular affine equivariant minimax estimator of –1 is inadmissible and an improved estimator is explicitly constructed. Note that our improved estimator is obtained from the class of lower-triangular scale equivariant estimators.  相似文献   

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