The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

Page 1

Displaying 1 – 11 of 11

Showing per page

Random fractals generated by a local Gaussian process indexed by a class of functions

Claire Coiffard (2012)

ESAIM: Probability and Statistics

In this paper, we extend the results of Orey and Taylor [S. Orey and S.J. Taylor, How often on a Brownian path does the law of the iterated logarithm fail? Proc. London Math. Soc.28 (1974) 174–192] relative to random fractals generated by oscillations of Wiener processes to a multivariate framework. We consider a setup where Gaussian processes are indexed by classes of functions.

Random fractals generated by a local gaussian process indexed by a class of functions

Claire Coiffard (2011)

ESAIM: Probability and Statistics

In this paper, we extend the results of Orey and Taylor [S. Orey and S.J. Taylor, How often on a Brownian path does the law of the iterated logarithm fail? Proc. London Math. Soc. 28 (1974) 174–192] relative to random fractals generated by oscillations of Wiener processes to a multivariate framework. We consider a setup where Gaussian processes are indexed by classes of functions.

Refinement type equations: sources and results

Rafał Kapica, Janusz Morawiec (2013)

Banach Center Publications

It has been proved recently that the two-direction refinement equation of the form f ( x ) = n c n , 1 f ( k x - n ) + n c n , - 1 f ( - k x - n ) can be used in wavelet theory for constructing two-direction wavelets, biorthogonal wavelets, wavelet packages, wavelet frames and others. The two-direction refinement equation generalizes the classical refinement equation f ( x ) = n c f ( k x - n ) , which has been used in many areas of mathematics with important applications. The following continuous extension of the classical refinement equation f ( x ) = c ( y ) f ( k x - y ) d y has also various interesting applications....

Restrictions of smooth functions to a closed subset

Shuzo Izumi (2004)

Annales de l’institut Fourier

We first provide an approach to the conjecture of Bierstone-Milman-Pawłucki on Whitney’s problem on C d extendability of functions. For example, the conjecture is affirmative for classical fractal sets. Next, we give a sharpened form of Spallek’s theorem on flatness.

Run-length function of the Bolyai-Rényi expansion of real numbers

Rao Li, Fan Lü, Li Zhou (2024)

Czechoslovak Mathematical Journal

By iterating the Bolyai-Rényi transformation T ( x ) = ( x + 1 ) 2 ( mod 1 ) , almost every real number x [ 0 , 1 ) can be expanded as a continued radical expression x = - 1 + x 1 + x 2 + + x n + with digits x n { 0 , 1 , 2 } for all n . For any real number x [ 0 , 1 ) and digit i { 0 , 1 , 2 } , let r n ( x , i ) be the maximal length of consecutive i ’s in the first n digits of the Bolyai-Rényi expansion of x . We study the asymptotic behavior of the run-length function r n ( x , i ) . We prove that for any digit i { 0 , 1 , 2 } , the Lebesgue measure of the set D ( i ) = x [ 0 , 1 ) : lim n r n ( x , i ) log n = 1 log θ i is 1 , where θ i = 1 + 4 i + 1 . We also obtain that the level set E α ( i ) = x [ 0 , 1 ) : lim n r n ( x , i ) log n = α is of full Hausdorff dimension...

Currently displaying 1 – 11 of 11

Page 1