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The purpose of this paper is to represent the integral Hankel transform as a series. If one uses B-spline wavelet this series is a linear combination of the hypergeometrical functions. Numerical evaluation of the test function with known…

Numerical Analysis · Mathematics 2025-10-20 Eugene B. Postnikov

We call $i$ a fixed point of a given sequence if the value of that sequence at the $i$-th position coincides with $i$. Here, we enumerate fixed points in the class of restricted growth sequences. The counting process is conducted by…

Combinatorics · Mathematics 2021-06-25 Toufik Mansour , Reza Rastegar

The main objective of this paper is to define the mother wavelet on local fields and study the continuous wavelet transform (CWT) and some of their basic properties. its inversion formula, the Parseval relation and associated convolution…

Functional Analysis · Mathematics 2015-01-30 Ashish Pathak

Time series foundation models (TSFMs) have recently achieved remarkable success in universal forecasting by leveraging large-scale pretraining on diverse time series data. Complementing this progress, incorporating frequency-domain…

Machine Learning · Computer Science 2026-04-14 Shunyu Wu , Jiawei Huang , Weibin Feng , Boxin Li , Xiao Zhang , Erli Meng , Dan Li , Jian Lou , See-Kiong Ng

In this paper we consider the continuous wavelet transform using Gaussian wavelets multiplied by an appropriate rational term. The zeros and poles of this rational modifier act as free parameters and their choice highly influences the shape…

Machine Learning · Statistics 2026-01-30 Attila Miklós Ámon , Kristian Fenech , Péter Kovács , Tamás Dózsa

The selection of grouped variables using the random forest algorithm is considered. First a new importance measure adapted for groups of variables is proposed. Theoretical insights into this criterion are given for additive regression…

Methodology · Statistics 2015-05-20 Baptiste Gregorutti , Bertrand Michel , Philippe Saint-Pierre

An invex function generalizes a convex function in the sense that every stationary point is a global minimizer. Recently, invex functions and their subclasses have attracted attention in signal processing and machine learning. However,…

Optimization and Control · Mathematics 2026-04-06 Akatsuki Nishioka

Continuous wavelet design is the endeavor to construct mother wavelets with desirable properties for the continuous wavelet transform (CWT). One class of methods for choosing a mother wavelet involves minimizing a functional, called the…

Functional Analysis · Mathematics 2023-07-20 Simon Halvdansson , Jan-Fredrik Olsen , Nir Sochen , Ron Levie

Let Y be a response variable related with a set of explanatory variables and let f1, f2, ..., fk be a set of the parametric forms representing a set of candidate's model. Let f* be the true model among the set of k plausible models. We…

We develop an exact wavelet transform on the three-dimensional ball (i.e. on the solid sphere), which we name the flaglet transform. For this purpose we first construct an exact transform on the radial half-line using damped Laguerre…

Information Theory · Computer Science 2013-08-15 B. Leistedt , J. D. McEwen

This paper provides central limit theorems for the wavelet packet decomposition of stationary band-limited random processes. The asymptotic analysis is performed for the sequences of the wavelet packet coefficients returned at the nodes of…

Information Theory · Computer Science 2009-10-26 Abdourrahmane Atto , Dominique Pastor

A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with…

Machine Learning · Computer Science 2016-05-04 Joan Bruna , Soumith Chintala , Yann LeCun , Serkan Piantino , Arthur Szlam , Mark Tygert

This article introduces the class of continuous time locally stationary wavelet processes. Continuous time models enable us to properly provide scale-based time series models for irregularly-spaced observations for the first time, while…

Statistics Theory · Mathematics 2025-03-19 Henry Antonio Palasciano , Marina I. Knight , Guy P. Nason

In this paper, the frequency-domain sound field is regarded as an element of some band-limited function space, and a representation of the field as a linear combination of the reproducing kernel in that space is proposed. This model has the…

Sound · Computer Science 2024-05-24 Takahiro Iwami , Akira Omoto

It is the main goal of this article to address the bipartite ranking issue from the perspective of functional data analysis (FDA). Given a training set of independent realizations of a (possibly sampled) second-order random function with a…

Machine Learning · Statistics 2013-12-19 Stéphan Clémençon , Marine Depecker

In this paper we study the general reconstruction of a compactly supported function from its Fourier coefficients using compactly supported shearlet systems. We assume that only finitely many Fourier samples of the function are accessible…

Functional Analysis · Mathematics 2015-07-31 Jackie Ma

We construct spherical wavelets based on approximate identities that are directional, i.e. not rotation-invariant, and have an adaptive angular selectivity. The problem of how to find a proper representation of distinct kinds of details of…

Classical Analysis and ODEs · Mathematics 2018-04-10 Ilona Iglewska-Nowak

An extremely simple single-trace transmission example shows how an extended source formulation of full waveform inversion can produce an optimization problem without spurious local minima ("cycle skipping"). The data consist of a single…

Geophysics · Physics 2020-04-03 William W. Symes

We introduce a definition of a quasiconvex function on an infinite directed regular tree that depends on what we understood by a segment on the tree. Our definition is based on thinking on segments as sub-trees with the root as the midpoint…

Analysis of PDEs · Mathematics 2024-04-03 Leandro M. Del Pezzo , Nicolas Frevenza , Julio D. Rossi

This paper introduces WaveNet, a deep neural network for generating raw audio waveforms. The model is fully probabilistic and autoregressive, with the predictive distribution for each audio sample conditioned on all previous ones;…