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In this note, we study the convergence from the discrete to the continuous non-linear Fourier transform. Relations between spectral problems and questions in complex function theory provide a new approach to the study of scattering problems…

Classical Analysis and ODEs · Mathematics 2024-08-16 Ashley R. Zhang

The Number Theoretic Transform (NTT) can be regarded as a variant of the Discrete Fourier Transform. NTT has been quite a powerful mathematical tool in developing Post-Quantum Cryptography and Homomorphic Encryption. The Fourier Transform…

Cryptography and Security · Computer Science 2025-09-09 Banhirup Sengupta , Peenal Gupta , Souvik Sengupta

The Iterative Filtering method is a technique aimed at the decomposition of non-stationary and non-linear signals into simple oscillatory components. This method, proposed a decade ago as an alternative technique to the Empirical Mode…

Numerical Analysis · Mathematics 2021-11-24 Antonio Cicone , Stefano Serra-Capizzano , Haomin Zhou

Data compression capability of "Compressed sensing (sampling)" in signal discretization is numerically evaluated and found to be far from the theoretical upper bound defined by signal sparsity. It is shown that, for the cases when ordinary…

Optics · Physics 2015-02-10 L. Yaroslavsky

This paper addresses the problem of expressing a signal as a sum of frequency components (sinusoids) wherein each sinusoid may exhibit abrupt changes in its amplitude and/or phase. The Fourier transform of a narrow-band signal, with a…

Machine Learning · Computer Science 2013-02-27 Yin Ding , Ivan W. Selesnick

Computer representations of real numbers are necessarily discrete, with some finite resolution, discreteness, quantization, or minimum representable difference. We perform astrometric and photometric measurements on stars and co-add…

Instrumentation and Methods for Astrophysics · Physics 2014-11-20 Adrian M. Price-Whelan , David W. Hogg

Spatial variables can be observed in many different forms, such as regularly sampled random fields (lattice data), point processes, and randomly sampled spatial processes. Joint analysis of such collections of observations is clearly…

Methodology · Statistics 2026-05-20 Jake P. Grainger , Tuomas A. Rajala , David J. Murrell , Sofia C. Olhede

This survey addresses sampling discretization and its connections with other areas of mathematics. The survey concentrates on sampling discretization of norms of elements of finite-dimensional subspaces. We present here known results on…

Functional Analysis · Mathematics 2022-02-11 B. Kashin , E. Kosov , I. Limonova , V. Temlyakov

Directional transforms have recently raised a lot of interest thanks to their numerous applications in signal compression and analysis. In this letter, we introduce a generalization of the discrete Fourier transform, called steerable DFT…

Information Theory · Computer Science 2017-03-16 Giulia Fracastoro , Enrico Magli

We investigate power spectra of a randomly sampled stationary stochastic signal, e.g. a spatial component of a turbulent velocity. We extend the methods of previous authors that basically assumed point or delta function sampling by…

Fluid Dynamics · Physics 2019-06-14 Preben Buchhave , Clara M. Velte , William K. George

This is basically a review of the field of Quasi-Monte Carlo intended for computational physicists and other potential users of quasi-random numbers. As such, much of the material is not new, but is presented here in a style hopefully more…

High Energy Physics - Phenomenology · Physics 2010-11-11 Fred James , Jiri Hoogland , Ronald Kleiss

A new integral identity for functions with continuous second partial derivatives is derived. It is shown that the value of any function f(r,t) at position r and time t is completely determined by its previous values at all other locations…

Quantum Physics · Physics 2015-05-18 J. D. Franson

Sample patterns have many uses in Computer Graphics, ranging from procedural object placement over Monte Carlo image synthesis to non-photorealistic depiction. Their properties such as discrepancy, spectra, anisotropy, or progressiveness…

Graphics · Computer Science 2018-06-19 Thomas Leimkühler , Gurprit Singh , Karol Myszkowski , Hans-Peter Seidel , Tobias Ritschel

Phaseless super-resolution refers to the problem of superresolving a signal from only its low-frequency Fourier magnitude measurements. In this paper, we consider the phaseless super-resolution problem of recovering a sum of sparse Dirac…

Information Theory · Computer Science 2016-09-28 Myung Cho , Christos Thrampoulidis , Weiyu Xu , Babak Hassibi

This brief note aims at condensing some results on the 32-point approximate DFT and discussing its arithmetic complexity.

Signal Processing · Electrical Eng. & Systems 2024-08-01 R. J. Cintra

Fractional processes have gained popularity in financial modeling due to the dependence structure of their increments and the roughness of their sample paths. The non-Markovianity of these processes gives, however, rise to conceptual and…

Mathematical Finance · Quantitative Finance 2018-02-07 Philipp Harms , David Stefanovits

Digital filters with variable bandwidth can be used for a variety of applications. Arbitrary change in the bandwidth of a digital Finite Impulse Response (FIR) filter can be acquired using sampling rate converters. In this paper, a sampling…

Signal Processing · Electrical Eng. & Systems 2021-09-27 Sushmitha Sajeevu , V. Sakthivel

We present a decomposition of finitely supported filters ( aka instrument function PSF) as a composition of invertible and non-invertible filters. The invertible component can be inverted directly and the non-invertible component is shown…

Numerical Analysis · Mathematics 2022-05-17 Yury Tyurin , Anastasia Tyurina

Addressing the optical communication systems employing the nonlinear Fourier transform (NFT) for the data modulation/demodulation, we provide an explicit proof for the properties of the signals emerging in the so-called b-modulation method,…

Exactly Solvable and Integrable Systems · Physics 2020-01-28 Dmitry Shepelsky , Anastasiia Vasylchenkova , Jaroslaw E. Prilepsky , Iryna Karpenko

The problem of computing the Fourier Transform of a signal whose spectrum is dominated by a small number $k$ of frequencies quickly and using a small number of samples of the signal in time domain (the Sparse FFT problem) has received…

Data Structures and Algorithms · Computer Science 2017-08-18 Michael Kapralov
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