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We perform Wigner analysis of linear operators. Namely, the standard time-frequency representation \emph{Short-time Fourier Transform} (STFT) is replaced by the $\mathcal{A}$-\emph{Wigner distribution} defined by $W_{\mathcal A}…

Analysis of PDEs · Mathematics 2021-08-10 Elena Cordero , Luigi Rodino

Sampling theory in fractional Fourier Transform (FrFT) domain has been studied extensively in the last decades. This interest stems from the ability of the FrFT to generalize the traditional Fourier Transform, broadening the traditional…

Information Theory · Computer Science 2024-04-30 Václav Pavlíček , Ayush Bhandari

The Fast Fourier Transform (FFT) is an algorithm of paramount importance in signal processing as it allows to apply the Fourier transform in O(n log n) instead of O(n 2) arithmetic operations. Graph Signal Processing (GSP) is a recent…

Numerical Analysis · Computer Science 2017-06-19 Luc Le Magoarou , Rémi Gribonval , Nicolas Tremblay

The synchrosqueezing transform, a kind of reassignment method, aims to sharpen the time-frequency representation and to separate the components of a multicomponent non-stationary signal. In this paper, we consider the short-time Fourier…

Signal Processing · Electrical Eng. & Systems 2019-09-27 Lin Li , Haiyan Cai , Hongxia Han , Qingtang Jiang , Hongbing Ji

With the increasing demand for multi-carrier communication in high-mobility scenarios, it is urgent to design new multi-carrier communication waveforms that can resist large delay-Doppler spreads. Various multi-carrier waveforms in the…

Signal Processing · Electrical Eng. & Systems 2024-06-05 Xingyao Zhang , Haoran Yin , Yanqun Tang , Yu Zhou , Yuqing Liu , Jinming Du , Yipeng Ding

In this paper we investigate new results on the theory of superoscillations using time-frequency analysis tools and techniques such as the short-time Fourier transform (STFT) and the Zak transform. We start by studying how the short-time…

Functional Analysis · Mathematics 2024-07-18 Daniel Alpay , Antonino De Martino , Kamal Diki , Daniele C. Struppa

The shift operation plays a crucial role in the classical signal processing. It is the generator of all the filters and the basic operation for time-frequency analysis, such as windowed Fourier transform and wavelet transform. With the…

Signal Processing · Electrical Eng. & Systems 2022-04-04 Lihua Yang , Qing Zhang , Qian Zhang , Chao Huang

The properties of the Gabor and Morlet transforms are examined with respect to the Fourier analysis of discretely sampled data. Forward and inverse transform pairs based on a fixed window with uniform sampling of the frequency axis can…

Data Analysis, Statistics and Probability · Physics 2013-07-23 Robert W. Johnson

In this paper, an algorithm for Quantum Inverse Fast Fourier Transform (QIFFT) is developed to work for quantum data. Analogous to a classical discrete signal, a quantum signal can be represented in Dirac notation, application of QIFFT is a…

Quantum Physics · Physics 2024-09-13 Mayank Roy , Devi Maheswaran

The achievable data rates of current fiber-optic wavelength-division-multiplexing (WDM) systems are limited by nonlinear interactions between different subchannels. Recently, it was thus proposed to replace the conventional Fourier…

Information Theory · Computer Science 2015-01-27 Sander Wahls , H. Vincent Poor

In recent years, the synchrosqueezing transform (SST) has gained popularity as a method for the analysis of signals that can be broken down into multiple components determined by instantaneous amplitudes and phases. One such version of SST,…

Numerical Analysis · Mathematics 2017-09-20 Alexander Berrian , Naoki Saito

In Graph Signal Processing (GSP), data dependencies are represented by a graph whose nodes label the data and the edges capture dependencies among nodes. The graph is represented by a weighted adjacency matrix $A$ that, in GSP, generalizes…

Signal Processing · Electrical Eng. & Systems 2020-12-02 João Domingos , José M. F. Moura

Certain signal classes such as audio signals call for signal representations with the ability to adapt to the signal's properties. In this article we introduce the new concept of quilted frames, which aim at adaptivity in time-frequency…

Functional Analysis · Mathematics 2010-01-25 Monika Doerfler

Fusion frames are extensively studied due to their effectiveness in recovering signals from large-scale data. They are applicable in distributed processing, wireless sensor networks, and packet encoding systems due to their robustness and…

Functional Analysis · Mathematics 2025-08-26 Avinash Bhardwaj , Animesh Bhandari

We propose a novel framework for fast integral operations by uncovering hidden geometries in the row and column structures of the underlying operators. This is accomplished through the \texttt{Questionnaire} algorithm, an iterative…

Numerical Analysis · Mathematics 2026-02-27 Pei-Chun Su , Ronald R. Coifman

The artificial noise (AN) aided multi-beam directional modulation (DM) technology is capable of wireless physical layer secure (PLS) transmissions for multiple desired receivers in free space. The application of AN, however, makes it less…

Signal Processing · Electrical Eng. & Systems 2019-08-14 Qian Cheng , Vincent Fusco , Jiang Zhu , Shilian Wang , Fanggang Wang

Fast Fourier Transforms (FFTs) are exploited in a wide variety of fields ranging from computer science to natural sciences and engineering. With the rising data production bandwidths of modern FFT applications, judging best which…

Performance · Computer Science 2017-07-12 Peter Steinbach , Matthias Werner

In this paper, we define a new transform called the Gabor quaternionic Fourier transform (GQFT), which generalizes the classical windowed Fourier transform to quaternion valued-signals, we give several important properties such as the…

Classical Analysis and ODEs · Mathematics 2019-01-07 Mohammed El Kassimi , Said Fahlaoui

Time-frequency representation (TFR) allowing for mode reconstruction plays a significant role in interpreting and analyzing the nonstationary signal constituted of various modes. However, it is difficult for most previous methods to handle…

Signal Processing · Electrical Eng. & Systems 2021-09-01 Haijian Zhang , Guang Hua

Modeling non-stationary processes, where statistical properties vary across the input domain, is a critical challenge in machine learning; yet most scalable methods rely on a simplifying assumption of stationarity. This forces a difficult…

Machine Learning · Computer Science 2026-02-03 Sawan Kumar , Souvik Chakraborty