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Fourier transform methods are used to analyze functions and data sets to provide frequencies, amplitudes, and phases of underlying oscillatory components. Fast Fourier transform (FFT) methods offer speed advantages over evaluation of…

Data Analysis, Statistics and Probability · Physics 2015-07-08 Elya Courtney , Michael Courtney

This paper develops a constructive numerical scheme for Fourier-Bessel approximations on disks compatible with convolutions supported on disks. We address accurate finite Fourier-Bessel transforms (FFBT) and inverse finite Fourier-Bessel…

Numerical Analysis · Mathematics 2023-11-08 Arash Ghaani Farashahi , Gregory S. Chirikjian

We introduce a Fourier-based fast algorithm for Gaussian process regression in low dimensions. It approximates a translationally-invariant covariance kernel by complex exponentials on an equispaced Cartesian frequency grid of $M$ nodes.…

Computation · Statistics 2023-05-19 Philip Greengard , Manas Rachh , Alex Barnett

- In this paper we present a method to compute the coefficients of the fractional Fourier transform (FrFT) on a quantum computer using quantum gates of polynomial complexity of the order O(n^3). The FrFt, a generalization of the DFT, has…

Quantum Physics · Physics 2009-06-08 Srinivas V. Parasa , K. Eswaran

We introduce a quantum algorithm to perform the Laplace transform on quantum computers. Already, the quantum Fourier transform (QFT) is the cornerstone of many quantum algorithms, but the Laplace transform or its discrete version has not…

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 Number Theoretic Transform (NTT) is a critical computational bottleneck in many lattice-based postquantum cryptographic (PQC) algorithms. By leveraging the Fast Fourier Transform (FFT) algorithm, the NTT of a polynomial of degree N - 1…

Cryptography and Security · Computer Science 2026-01-27 Mohammed Nabeel , Mahmoud Hafez , Michail Maniatakos

We consider the problem of computing the Walsh-Hadamard Transform (WHT) of some $N$-length input vector in the presence of noise, where the $N$-point Walsh spectrum is $K$-sparse with $K = {O}(N^{\delta})$ scaling sub-linearly in the input…

Information Theory · Computer Science 2015-08-27 Xiao Li , Joseph K. Bradley , Sameer Pawar , Kannan Ramchandran

Affine frequency division multiplexing (AFDM) and orthogonal AFDM access (O-AFDMA) are promising techniques based on chirp signals, which are able to suppress the performance deterioration caused by Doppler shifts in high-mobility…

Information Theory · Computer Science 2024-05-07 Yiwei Tao , Miaowen Wen , Yao Ge , Tianqi Mao , Lixia Xiao , Jun Li

Homomorphic encryption (HE) draws huge attention as it provides a way of privacy-preserving computations on encrypted messages. Number Theoretic Transform (NTT), a specialized form of Discrete Fourier Transform (DFT) in the finite field of…

Cryptography and Security · Computer Science 2020-12-04 Sangpyo Kim , Wonkyung Jung , Jaiyoung Park , Jung Ho Ahn

The fundamentals of Fourier Transform are presented, with analytical solutions derived for Continuous Fourier Transform (CFT) of truncated signals, to benchmark against Fast Fourier Transform (FFT). Certain artifacts from FFT were…

Applied Physics · Physics 2019-07-03 K. H. H. Goh

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

Channel estimation is one of the most important parts in current mobile communication systems. Among the huge contributions in channel estimation studies, the discrete Fourier transform (DFT)-based channel estimation has attracted lots of…

Information Theory · Computer Science 2015-04-29 H. Yu , C. Yang

A Fast algorithm for the Discrete Hartley Transform (DHT) is presented, which resembles radix-2 fast Fourier Transform (FFT). Although fast DHTs are already known, this new approach bring some light about the deep relationship between fast…

Discrete Mathematics · Computer Science 2015-03-13 H. M. de Oliveira , V. L. Sousa , H. A. N. , R. M. Campello de Souza

The Fast Fourier Transform (FFT) is a computationally intensive digital signal processing (DSP) function widely used in applications such as imaging, software-defined radio, wireless communication, instrumentation. In this paper, a…

Other Computer Science · Computer Science 2010-06-15 Ashish Raman , Anvesh Kumar , R. K. Sarin

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

To investigate neural network parameters, it is easier to study the distribution of parameters than to study the parameters in each neuron. The ridgelet transform is a pseudo-inverse operator that maps a given function $f$ to the parameter…

Machine Learning · Computer Science 2024-04-22 Sho Sonoda , Isao Ishikawa , Masahiro Ikeda

This paper introduces the theory and hardware implementation of two new algorithms for computing a single component of the discrete Fourier transform. In terms of multiplicative complexity, both algorithms are more efficient, in general,…

Discrete Mathematics · Computer Science 2018-01-24 G. Jerônimo da Silva , R. M. Campello de Souza , H. M. de Oliveira

Starting from a comparison of some established numerical algorithms for the computation of the eigenvalues (discrete or solitonic spectrum) of the non-Hermitian version of the Zakharov-Shabat spectral problem, this article delivers new…

Numerical Analysis · Mathematics 2018-09-11 A. Vasylchenkova , J. E. Prilepsky , D. Shepelsky , A. Chattopadhyay

Foundation models have achieved tremendous success in different domains. However, their huge computation and storage complexity make these models difficult to fine-tune and also less applicable in practice. Recent study shows training in…

Machine Learning · Computer Science 2025-07-16 Xinyu Ding , Lexuan Chen , Siyu Liao , Zhongfeng Wang