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DFT is the numerical implementation of Fourier transform (FT), and it has many forms. Ordinary DFT (ODFT) and symmetric DFT (SDFT) are the two main forms of DFT. The most widely used DFT is ODFT, and the phase spectrum of this form is…

Information Theory · Computer Science 2021-08-27 Rui Li

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

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

We consider the problem of finding the Discrete Fourier Transform (DFT) of $N-$ length signals with known frequency support of size $k$. When $N$ is a power of 2 and the frequency support is a spectral set, we provide an $O(k \log k)$…

Signal Processing · Electrical Eng. & Systems 2021-10-07 P Charantej Reddy , V S S Prabhu Tej , Aditya Siripuram , Brad Osgood

This paper concerns the fast evaluation of the matvec $g=Kf$ for $K\in \mathbb{C}^{N\times N}$, which is the discretization of the oscillatory integral transform $g(x) = \int K(x,\xi) f(\xi)d\xi$ with a kernel function…

Numerical Analysis · Mathematics 2019-05-01 Haizhao Yang

Quantum computing with qudits, quantum systems with $d > 2$ levels, offers a powerful extension beyond qubits, expanding the computational possibilities of quantum systems, allowing the simplification of the implementation of several…

Quantum Physics · Physics 2024-10-10 Francesco Pudda , Mario Chizzini , Luca Crippa

Fast Fourier Transform (FFT) is an efficient algorithm to compute the Discrete Fourier Transform (DFT) and its inverse. In this paper, we pay special attention to the description of complex-data FFT. We analyze two common descriptions of…

Numerical Analysis · Computer Science 2011-10-28 Zhengjun Cao , Xiao Fan

Symmetry learning has proven to be an effective approach for extracting the hidden structure of data, with the concept of equivariance relation playing the central role. However, most of the current studies are built on architectural theory…

Machine Learning · Statistics 2024-02-15 Masanori Koyama , Kenji Fukumizu , Kohei Hayashi , Takeru Miyato

Discrete transforms such as the discrete Fourier transform (DFT) and the discrete Hartley transform (DHT) are important tools in numerical analysis. The successful application of transform techniques relies on the existence of efficient…

Numerical Analysis · Computer Science 2015-02-06 H. M. de Oliveira , R. J. Cintra , R. M. Campello de Souza

The nonlinear Fourier transform (NFT), a powerful tool in soliton theory and exactly solvable models, is a method for solving integrable partial differential equations governing wave propagation in certain nonlinear media. The NFT…

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

Optoacoustic imaging technologies require fast and accurate signal pre-processing algorithms to enable widespread deployment in clinical and home-care settings. However, they still rely on the Discrete Fourier Transform (DFT) as the default…

To reach the next frontier in multimode nonlinear optics, it is crucial to better understand the classical and quantum phenomena of systems with many interacting degrees of freedom -- both how they emerge and how they can be tailored to…

We defined a non-commutative algebra representation for quantum systems whose phase space is the cotangent bundle of the Lorentz group, and the non-commutative Fourier transform ensuring the unitary equivalence with the standard group…

High Energy Physics - Theory · Physics 2019-05-22 Daniele Oriti , Giacomo Rosati

In many processes, the variations in underlying characteristics can be approximated by noisy multi-periodic patterns. If large-scale patterns are superimposed by a noise with long-range correlations, the detection of multi-periodic patterns…

Quantitative Methods · Quantitative Biology 2019-12-09 V. R. Chechetkin , V. V. Lobzin

In this paper we consider Sparse Fourier Transform (SFT) algorithms for approximately computing the best $s$-term approximation of the Discrete Fourier Transform (DFT) $\mathbf{\hat{f}} \in \mathbb{C}^N$ of any given input vector…

Numerical Analysis · Mathematics 2017-06-12 Sami Merhi , Ruochuan Zhang , Mark A. Iwen , Andrew Christlieb

Convolutional Neural Networks (CNN) have been successful in processing data signals that are uniformly sampled in the spatial domain (e.g., images). However, most data signals do not natively exist on a grid, and in the process of being…

Computer Vision and Pattern Recognition · Computer Science 2019-01-09 Chiyu "Max" Jiang , Dequan Wang , Jingwei Huang , Philip Marcus , Matthias Nießner

The nonlinear Fourier transform (NFT) decomposes waveforms propagating through optical fiber into nonlinear degrees of freedom, which are preserved during transmission. By encoding information on the nonlinear spectrum, a transmission…

Signal Processing · Electrical Eng. & Systems 2020-12-24 Jan-Willem Goossens , Hartmut Hafermann , Yves Jaouën

Although Fourier series approximation is ubiquitous in computational physics owing to the Fast Fourier Transform (FFT) algorithm, efficient techniques for the fast evaluation of a three-dimensional truncated Fourier series at a set of…

Numerical Analysis · Mathematics 2017-03-08 Marco Caliari , Simone Zuccher

We unify the discrete Fourier transform (DFT), discrete cosine transform (DCT), Walsh-Hadamard, Haar wavelet, Karhunen-Lo\`eve transform, and several others along with their continuous counterparts (Fourier transform, Fourier series,…

Signal Processing · Electrical Eng. & Systems 2026-05-19 Mitchell A. Thornton

We present a discrete-time algorithm for nonuniform sampling rate conversion that presents low computational complexity and memory requirements. It generalizes arbitrary sampling rate conversion by accommodating time-varying conversion…

Signal Processing · Electrical Eng. & Systems 2021-05-17 Pablo Martínez-Nuevo