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We derive the almost sure Assouad spectrum and quasi-Assouad dimension of random self-affine Bedford-McMullen carpets. Previous work has revealed that the (related) Assouad dimension is not sufficiently sensitive to distinguish between…

Dynamical Systems · Mathematics 2023-06-22 Jonathan M. Fraser , Sascha Troscheit

In a previous paper we introduced a new `dimension spectrum', motivated by the Assouad dimension, designed to give precise information about the scaling structure and homogeneity of a metric space. In this paper we compute the spectrum…

Classical Analysis and ODEs · Mathematics 2019-06-10 Jonathan M. Fraser , Han Yu

We characterise interpolating and sampling sequences for the spaces of entire functions f such that f e^{-phi} belongs to L^p(C), p>=1 (and some related weighted classes), where phi is a subharmonic weight whose Laplacian is a doubling…

Complex Variables · Mathematics 2007-05-23 Nicolas Marco , Xavier Massaneda , Joaquim Ortega-Cerdà

The notion of different kind of algebraic Casorati curvatures are introduced. Some results expressing basic Casorati inequalities for algebraic Casorati curvatures are presented. Equality cases are also discussed. As a simple application,…

Differential Geometry · Mathematics 2016-07-21 Mukut Mani Tripathi

This article deals with (1) the construction of a general non-linear fractal interpolation function on PCF self-similar sets, (2) the energy and normal derivatives of uniform non-linear fractal functions, (3) estimation of the bound of box…

Dynamical Systems · Mathematics 2025-05-16 Aaryan Dharmesh Shah , Sangita Jha , Anarul Islam Mondal

We study the packing dimension of Borel measures under orthogonal projections. We give a necessary and sufficient condition such that typical projections of Borel probability measures have full packing dimension and derive general lower…

Classical Analysis and ODEs · Mathematics 2026-04-21 Nicolas Angelini

The connection between continued fractions and orthogonality which is familiar for $J$-fractions and $T$-fractions is extended to what we call $R$-fractions of type I and II. These continued fractions are associated with recurrence…

Classical Analysis and ODEs · Mathematics 2008-02-03 Mourad E. H. Ismail , David R. Masson

We consider a Froeschl\'e map and we add a weak dissipation of the form $\lambda(\varepsilon) = 1- \varepsilon^3$, where $\varepsilon$ is the parameter of perturbation. We compute formal expansions of lower dimensional tori, both in the…

Dynamical Systems · Mathematics 2024-07-09 Adrián P. Bustamante

We consider near-critical two-dimensional statistical systems at phase coexistence on the half plane with boundary conditions leading to the formation of a droplet separating coexisting phases. General low-energy properties of…

Statistical Mechanics · Physics 2022-12-02 Alessio Squarcini , Antonio Tinti

We consider a construction of recurrent fractal interpolation surfaces with function vertical scaling factors and estimation of their box-counting dimension. A recurrent fractal interpolation surface (RFIS) is an attractor of a recurrent…

Dynamical Systems · Mathematics 2013-07-12 Chol-Hui Yun , Hui-Chol Choi , Hyong-Chol O

The recovery of the intrinsic geometric structures of data collections is an important problem in data analysis. Supervised extensions of several manifold learning approaches have been proposed in the recent years. Meanwhile, existing…

Computer Vision and Pattern Recognition · Computer Science 2018-05-29 Cem Ornek , Elif Vural

There has been a long history of works showing that neural networks have hard time extrapolating beyond the training set. A recent study by Balestriero et al. (2021) challenges this view: defining interpolation as the state of belonging to…

Machine Learning · Computer Science 2022-07-19 Laurent Bonnasse-Gahot

Metrics on Grassmannians have a wide array of applications: machine learning, wireless communication, computer vision, etc. But the available distances between subspaces of distinct dimensions present problems, and the dimensional asymmetry…

Algebraic Geometry · Mathematics 2022-08-11 André L. G. Mandolesi

We consider coherent sublinear expectations on a measurable space, without assuming the existence of a dominating probability measure. By considering a decomposition of the space in terms of the supports of the measures representing our…

Probability · Mathematics 2011-10-27 Samuel N. Cohen

We study the Hausdorff dimension of self-similar sets and measures on the line. We show that if the dimension is smaller than the minimum of 1 and the similarity dimension, then at small scales there are super-exponentially close cylinders.…

Classical Analysis and ODEs · Mathematics 2014-09-23 Michael Hochman

We study self-similar sets and measures on $\mathbb{R}^{d}$. Assuming that the defining iterated function system $\Phi$ does not preserve a proper affine subspace, we show that one of the following holds: (1) the dimension is equal to the…

Classical Analysis and ODEs · Mathematics 2017-06-07 Michael Hochman

Dimensions of level sets of generic continuous functions and generic H\"older functions defined on a fractal $F$ encode information about the geometry, ``the thickness" of $F$. While in the continuous case this quantity is related to a…

Classical Analysis and ODEs · Mathematics 2024-10-10 Zoltán Buczolich , Balázs Maga , Gáspár Vértesy

In this paper, we investigate the properties of symmetry in two variables related to multiple Euler q-l-function which interpolates higher-order q-Euler polynomials at negative integers. From our investigation, we can derive many…

Number Theory · Mathematics 2013-12-18 D. V. Dolgy , D. S. Kim , T. G. Kim , J. J. Seo

The problem of extrapolation and interpolation of asymptotic series is considered. Several new variants of improving the accuracy of the self-similar approximants are suggested. The methods are illustrated by examples typical of chemical…

Mathematical Physics · Physics 2010-04-08 V. I. Yukalov , E. P. Yukalova , S. Gluzman

The over-parameterized models attract much attention in the era of data science and deep learning. It is empirically observed that although these models, e.g. deep neural networks, over-fit the training data, they can still achieve small…

Machine Learning · Statistics 2019-09-27 Yue Xing , Qifan Song , Guang Cheng