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To comprehensively assess optical fiber communication system conditions, it is essential to implement joint estimation of the following four critical impairments: nonlinear signal-to-noise ratio (SNRNL), optical signal-to-noise ratio…

Signal Processing · Electrical Eng. & Systems 2023-08-29 Ting Jiang , Zheng Gao , Yizhao Chen , Zihe Hu , Ming Tang

The state-of-the-art automotive radars employ multidimensional discrete Fourier transforms (DFT) in order to estimate various target parameters. The DFT is implemented using the fast Fourier transform (FFT), at sample and computational…

Signal Processing · Electrical Eng. & Systems 2018-01-16 Shaogang Wang , Vishal M. Patel , Athina Petropulu

Optimizing modulation and detection strategies for a given channel is critical to maximize the throughput of a communication system. Such an optimization can be easily carried out analytically for channels that admit closed-form analytical…

Signal Processing · Electrical Eng. & Systems 2021-02-03 Simone Gaiarin , Francesco Da Ros , Rasmus T. Jones , Darko Zibar

In this paper, numerical methods are suggested to compute the discrete and the continuous spectrum of a signal with respect to the Zakharov-Shabat system, a Lax operator underlying numerous integrable communication channels including the…

Information Theory · Computer Science 2014-10-09 Mansoor I. Yousefi , Frank R. Kschischang

This paper is devoted to a discussion of the Discrete Fourier Transform (DFT) representation of a chaotic finite-duration sequence. This representation has the advantage that is itself a finite-duration sequence corresponding to samples…

Chaotic Dynamics · Physics 2007-05-23 Carlos R. Fadragas , Juan V. Lorenzo-Ginori , Ruben Orozco-Morales

The concept of Nonlinear dispersion relation (NDR) is used in various fields of Physics (nonlinear optics, hydrodynamics, hydroelasticity, mechanics, quantum optics, plasma physics,...) to characterize fundamental phenomena induced by…

The increasing complexity of neural networks and the energy consumption associated with training and inference create a need for alternative neuromorphic approaches, e.g. using optics. Current proposals and implementations rely on physical…

Optics · Physics 2023-08-31 Clara C. Wanjura , Florian Marquardt

In linear communication channels, spectral components (modes) defined by the Fourier transform of the signal propagate without interactions with each other. In certain nonlinear channels, such as the one modelled by the classical nonlinear…

Optics · Physics 2015-06-22 Son Thai Le , Jaroslaw E. Prilepsky , Sergei K. Turitsyn

A brief survey of the theory of soliton perturbations is presented. The focus is on the usefulness of the so-called Generalised Fourier Transform (GFT). This is a method that involves expansions over the complete basis of `squared olutions`…

Exactly Solvable and Integrable Systems · Physics 2009-07-30 Georgi G. Grahovski , Rossen I. Ivanov

Nonnegative matrix factorization (NMF) is a popular method for audio spectral unmixing. While NMF is traditionally applied to off-the-shelf time-frequency representations based on the short-time Fourier or Cosine transforms, the ability to…

Machine Learning · Statistics 2018-11-07 Pierre Ablin , Dylan Fagot , Herwig Wendt , Alexandre Gramfort , Cédric Févotte

We consider finite approximations of a fractal generated by an iterated function system of affine transformations on $\mathbb{R}^d$ as a discrete set of data points. Considering a signal supported on this finite approximation, we propose a…

Functional Analysis · Mathematics 2016-07-14 Calvin Hotchkiss , Eric S. Weber

The numerical simulation of wave propagation in semiclassical (high-frequency) problems is well known to pose a formidable challenge. In this work, a new phase-space approach for the numerical simulation of semiclassical wave propagation,…

Analysis of PDEs · Mathematics 2008-10-30 Agissilaos G. Athanassoulis

A global solution of the Schr\"odinger equation for explicitly time-dependent Hamiltonians is derived by integrating the non-linear differential equation associated with the time-dependent wave operator. A fast iterative solution method is…

Quantum Physics · Physics 2015-05-18 Arnaud Leclerc , Georges Jolicard

A simple least-squares optimisation enables the determination of the spectrum for irregularly sampled data that is readily reconstructed using an adjoint transformation of the Non-Uniform Fast Fourier Transform (NFFT). This is an…

Numerical Analysis · Mathematics 2024-02-28 Michael Sorochan Armstrong , José Carlos Pérez-Girón , José Camacho , Regino Zamora

A mechanism for asymmetric (nonreciprocal) wave transmission is presented. As a reference system, we consider a layered nonlinear, non mirror-symmetric model described by the one-dimensional Discrete Nonlinear Schreodinger equation with…

Pattern Formation and Solitons · Physics 2012-04-12 Stefano Lepri , Giulio Casati

Transfer learning (TL) is a powerful tool for enhancing the performance of neural networks (NNs) in applications such as weather and climate prediction and turbulence modeling. TL enables models to generalize to out-of-distribution data…

Machine Learning · Computer Science 2025-04-23 Moein Darman , Pedram Hassanzadeh , Laure Zanna , Ashesh Chattopadhyay

Optical turbulence modelling and simulation are crucial for developing astronomical ground-based instruments, laser communication, laser metrology, or any application where light propagates through a turbulent medium. In the context of…

Instrumentation and Methods for Astrophysics · Physics 2024-04-05 A. Berdja , M. Hadjara , M. Carbillet , R. L. Bernardi , R. G. Petrov

The plane wave method is most widely used for solving the Kohn-Sham equations in first-principles materials science computations. In this procedure, the three-dimensional (3-dim) trial wave functions' fast Fourier transform (FFT) is a…

Computational Physics · Physics 2018-01-17 Xingyu Gao , Zeyao Mo , Jun Fang , Han Wang

Plasmon-induced transparency (PIT) displays complex nonlinear dynamics that find critical phenomena in areas such as nonlinear waves. However, such a nonlinear solution depends sensitively on the selection of parameters and different…

Computational Physics · Physics 2021-08-11 Jiaxi Cheng , Zhenhao Cen , Siliu Xu

We introduce the Fourier Learning Machine (FLM), a neural network (NN) architecture designed to represent a multidimensional nonharmonic Fourier series. The FLM uses a simple feedforward structure with cosine activation functions to learn…

Machine Learning · Computer Science 2026-03-20 Mominul Rubel , Adam Meyers , Gabriel Nicolosi
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