Corrigendum and addendum to the paper "In general, Bernoulli convolutions have independent powers", Studia Math. 47 (1973), pp. 141-152

1977 ◽  
Vol 61 (1) ◽  
pp. 25-28
Author(s):  
Gavin Brown ◽  
William Morak
2005 ◽  
Vol 12 (4) ◽  
pp. 637-658
Author(s):  
Dorothee D. Haroske ◽  
Erika Tamási

Abstract This paper deals with wavelet frames in anisotropic Besov spaces , 𝑠 ∈ ℝ, 0 < 𝑝, 𝑞 ≤ ∞, and 𝑎 = (𝑎1, . . . , 𝑎𝑛) is an anisotropy, with 𝑎𝑖 > 0, 𝑖 = 1, . . . , 𝑛, 𝑎1 + . . . + 𝑎𝑛 = 𝑛. We present sub-atomic and wavelet decompositions for a large class of distributions. To some extent our results can be regarded as anisotropic counterparts of those recently obtained in [Triebel, Studia Math. 154: 59–88, 2003].


1996 ◽  
Vol 82 (1-2) ◽  
pp. 397-420 ◽  
Author(s):  
François Ledrappier ◽  
Anna Porzio

2015 ◽  
Vol 269 (5) ◽  
pp. 1571-1590 ◽  
Author(s):  
Li-Xiang An ◽  
Xing-Gang He ◽  
Hai-Xiong Li

2018 ◽  
Vol 2020 (19) ◽  
pp. 6569-6595 ◽  
Author(s):  
Shigeki Akiyama ◽  
De-Jun Feng ◽  
Tom Kempton ◽  
Tomas Persson

Abstract We give an expression for the Garsia entropy of Bernoulli convolutions in terms of products of matrices. This gives an explicit rate of convergence of the Garsia entropy and shows that one can calculate the Hausdorff dimension of the Bernoulli convolution $\nu _{\beta }$ to arbitrary given accuracy whenever $\beta $ is algebraic. In particular, if the Garsia entropy $H(\beta )$ is not equal to $\log (\beta )$ then we have a finite time algorithm to determine whether or not $\operatorname{dim_H} (\nu _{\beta })=1$.


2002 ◽  
Vol 87 (1) ◽  
pp. 337-367 ◽  
Author(s):  
Elon Lindenstrauss ◽  
Yuval Peres ◽  
Wilhelm Schlag

1994 ◽  
Vol 8 (4) ◽  
pp. 449-462 ◽  
Author(s):  
Erol A. Peköz ◽  
Sheldon M. Ross

Let X1,…, Xn, be indicator random variables, and set We present a method for estimating the distribution of W in settings where W has an approximately Poisson distribution. Our method is shown to yield estimates significantly better than straight Poisson estimates when applied to Bernoulli convolutions, urn models, the circular k of n: F system, and a matching problem. Error bounds are given.


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