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Understanding generalization in deep learning has been one of the major challenges in statistical learning theory over the last decade. While recent work has illustrated that the dataset and the training algorithm must be taken into account…

We propose the adaptive random Fourier features Gaussian kernel LMS (ARFF-GKLMS). Like most kernel adaptive filters based on stochastic gradient descent, this algorithm uses a preset number of random Fourier features to save computation…

Signal Processing · Electrical Eng. & Systems 2022-07-18 Wei Gao , Jie Chen , Cédric Richard , Wentao Shi , Qunfei Zhang

We propose a new algorithm for solving the graph-fused lasso (GFL), a method for parameter estimation that operates under the assumption that the signal tends to be locally constant over a predefined graph structure. Our key insight is to…

Machine Learning · Statistics 2015-06-02 Wesley Tansey , James G. Scott

We consider 3D versions of the Zernike polynomials that are commonly used in 2D in optics and lithography. We generalize the 3D Zernike polynomials to functions that vanish to a prescribed degree $\alpha\geq0$ at the rim of their supporting…

Classical Analysis and ODEs · Mathematics 2015-10-19 Augustus J. E. M. Janssen

Recent progress in synthetic aperture sonar (SAS) technology and processing has led to significant advances in underwater imaging, outperforming previously common approaches in both accuracy and efficiency. There are, however, inherent…

Numerical Analysis · Mathematics 2017-06-28 John McKay , Anne Gelb , Vishal Monga , Raghu Raj

This paper studies the approximation of generalized ridge functions, namely of functions which are constant along some submanifolds of $\mathbb{R}^N$. We introduce the notion of linear-sleeve functions, whose function values only depend on…

Numerical Analysis · Mathematics 2017-01-26 Sandra Keiper

Fuzzy systems (FSs) have enjoyed wide applications in various fields, including pattern recognition, intelligent control, data mining and bioinformatics, which is attributed to the strong interpretation and learning ability. In traditional…

Artificial Intelligence · Computer Science 2023-09-21 Fuping Hu , Zhaohong Deng , Zhenping Xie , Kup-Sze Choi , Shitong Wang

In this paper a sublinear time algorithm is presented for the reconstruction of functions that can be represented by just few out of a potentially large candidate set of Fourier basis functions in high spatial dimensions, a so-called…

Numerical Analysis · Mathematics 2020-06-24 Lutz Kämmerer , Felix Krahmer , Toni Volkmer

This study focuses on convex functions and their generalized. Thus, we start this study by giving the definition of convex functions and some of their properties and discussing a simple geometric property. Then we generalize E-convex…

Classical Analysis and ODEs · Mathematics 2017-04-27 Adem Kilicman , Wedad Saleh

Fourier series of smooth, non-periodic functions on $[-1,1]$ are known to exhibit the Gibbs phenomenon, and exhibit overall slow convergence. One way of overcoming these problems is by using a Fourier series on a larger domain, say $[-T,T]$…

Numerical Analysis · Computer Science 2015-09-02 Roel Matthysen , Daan Huybrechs

Dual feasible functions (DFFs) have been used to provide bounds for standard packing problems and valid inequalities for integer optimization problems. In this paper, the connection between general DFFs and a particular family of…

Optimization and Control · Mathematics 2018-12-04 Matthias Köppe , Jiawei Wang

A fast algorithm (linear in the degrees of freedom) for the solution of linear variable-coefficient rational-order fractional integral and differential equations is described. The approach is related to the ultraspherical method for…

Numerical Analysis · Mathematics 2017-12-04 Nicholas Hale , Sheehan Olver

Pulse Compression (PC) active sonar waveforms provide a significant improvement in range resolution over single frequency sinusoidal waveforms also known as Continuous Wave (CW) waveforms. Since their inception in the 1940's, a wide variety…

Signal Processing · Electrical Eng. & Systems 2018-10-01 David A. Hague

Nonuniformly sampled signals are prevalent in real-world applications. However, estimating their power spectra from finite samples poses a significant challenge. The optimal solution-Bronez Generalized Prolate Spheroidal Sequence (GPSS) by…

Signal Processing · Electrical Eng. & Systems 2025-12-24 Jie Cui , Benjamin H. Brinkmann , Gregory A. Worrell

This paper introduces a design method for densergraph-frequency graph Fourier frames (DGFFs) to enhance graph signal processing and analysis. The graph Fourier transform (GFT) enables us to analyze graph signals in the graph spectral domain…

Signal Processing · Electrical Eng. & Systems 2025-03-18 Kaito Nitani , Seisuke Kyochi

The one-dimensional (1D) fractional Fourier transform (FRFT) generalizes the Fourier transform, offering significant advantages in the time-frequency analysis of non-stationary signals. While various 2D extensions exist, such as the 2D…

Signal Processing · Electrical Eng. & Systems 2026-03-03 Daxiang Li , Zhichao Zhang , Wei Yao

We continue our study of the construction of analytical coefficients of the epsilon-expansion of hypergeometric functions and their connection with Feynman diagrams. In this paper, we apply the approach of obtaining iteratated solutions to…

High Energy Physics - Theory · Physics 2009-04-03 M. Yu. Kalmykov , B. F. L. Ward , S. A. Yost

Spherical harmonics (SH) have been extensively used as a basis for analyzing the morphology of particles in granular mechanics. The use of SH is facilitated by mapping the particle coordinates onto a unit sphere, in practice often a…

Soft Condensed Matter · Physics 2024-11-14 Mahmoud Shaqfa , Wim M. van Rees

One of the fundamental problems in communications is finding the energy distribution of signals in time and frequency domains. It should, therefore, be of great interest to find the most energy concentration hypercomplex signal. The present…

Classical Analysis and ODEs · Mathematics 2016-09-06 Cuiming Zou , Kit Ian Kou , Joao Morais

This paper introduces the generalized forward-backward splitting algorithm for minimizing convex functions of the form $F + \sum_{i=1}^n G_i$, where $F$ has a Lipschitz-continuous gradient and the $G_i$'s are simple in the sense that their…

Optimization and Control · Mathematics 2014-02-11 Hugo Raguet , Jalal Fadili , Gabriel Peyré
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