Titlebook: 50 Years with Hardy Spaces; A Tribute to Victor Anton Baranov,Sergei Kisliakov,Nikolai Nikolski Book 2018 Springer International Publishin

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https://doi.org/10.1007/978-3-658-35613-2= 0. In dimension . = 2 we refine the Donnelly–Fefferman estimate by showing that .1(. = 0}) .3.4. for some . (0, 1.4). The proof employs the Donnelly–Fefferman estimate and a combinatorial argument, which also gives a lower (non-sharp) bound in dimension . = 3: .2(. = 0.) . for some . (0,1.2). The

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50 Years with Hardy Spaces978-3-319-59078-3Series ISSN 0255-0156 Series E-ISSN 2296-4878

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Comparing Two-Sample Means or Proportions,|R.μ(.). sup .supp . |R.μ(.).= .(.). This relation was known for . 1 ., and is still an open problem in the general case. We prove the maximum principle for 0 . 1, and also for 0 . in the case of radial measure. Moreover, we show that this conjecture is incorrect for non-positive measures.

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https://doi.org/10.1007/978-1-4757-3814-8f talents, which still continues to bring forth new generations of bright scholars. Here we try to trace his way, describe his profound impact on our community, and simply sketch a few features of his unforgettable personality.

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Experimental Design and Data Analysis,s for maxima of .(1.2 + .). on long intervals, as well as work of Soundararajan, G´al, and others. The paper aims at displaying and clarifying the conceptually different combinatorial arguments that show up in various parts of the proofs.

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https://doi.org/10.1007/978-0-387-93837-0ment of the Abel–Poisson means by arbitrary approximate identities. One question caused by this development was whether the Abel–Poisson means are the only approximative identities that are asymptotically multiplicative on (.,.), and the review closes with Wolf and Havin’s theorem, which gives an affirmative answer to this question.

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