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This paper proposes a supervised dimension reduction methodology for tensor data which has two advantages over most image-based prognostic models. First, the model does not require tensor data to be complete which expands its application to…

Machine Learning · Computer Science 2023-06-06 Chengyu Zhou , Xiaolei Fang

In optical diffraction tomography (ODT), the three-dimensional scattering potential of a microscopic object rotating around its center is recovered by a series of illuminations with coherent light. Reconstruction algorithms such as the…

Numerical Analysis · Mathematics 2022-09-02 Robert Beinert , Michael Quellmalz

The Fast Fourier Transform(FFT) is a classic signal processing algorithm that is utilized in a wide range of applications. For image processing, FFT computes on every pixel's value of an image, regardless of their properties in frequency…

Signal Processing · Electrical Eng. & Systems 2020-02-25 Sheng Shi , Runkai Yang , Haihang You

Approximate methods have been considered as a means to the evaluation of discrete transforms. In this work, we propose and analyze a class of integer transforms for the discrete Fourier, Hartley, and cosine transforms (DFT, DHT, and DCT),…

Signal Processing · Electrical Eng. & Systems 2020-07-07 R. J. Cintra

Tensor decompositions have become essential tools for feature extraction and compression of multiway data. Recent advances in tensor operators have enabled desirable properties of standard matrix algebra to be retained for multilinear…

Numerical Analysis · Mathematics 2024-10-01 Katherine Keegan , Elizabeth Newman

Tensor completion refers to the task of estimating the missing data from an incomplete measurement or observation, which is a core problem frequently arising from the areas of big data analysis, computer vision, and network engineering. Due…

Machine Learning · Computer Science 2021-05-21 Chenjian Pan , Chen Ling , Hongjin He , Liqun Qi , Yanwei Xu

The oriented singular value decomposition (O-SVD) proposed by Zeng and Ng provides a hybrid approach to the t-product based third-order tensor singular value decomposition with the transform matrix being a factor matrix of the higher order…

Numerical Analysis · Mathematics 2023-02-28 Minghui Ding , Yimin Wei , Pengpeng Xie

In this paper, a new regularization term is proposed to solve mathematical image problems. By using difference operators in the four directions; horizontal, vertical and two diagonal directions, an estimation of derivative amplitude is…

Numerical Analysis · Mathematics 2022-09-14 Alireza Hosseini

The quantum Fourier transform for discrete variable (dvQFT) is an efficient algorithm for several applications. It is usually considered for the processing of quantum bits (qubits) and its efficient implementation is obtained with two…

Quantum Physics · Physics 2025-12-16 Gianfranco Cariolaro , Edi Ruffa , Amir Mohammad Yaghoobianzadeh , Jawad A. Salehi

We present direct logarithmically optimal in theory and fast in practice algorithms to implement the tensor product high order finite element method on multi-dimensional rectangular parallelepipeds for solving PDEs of the Poisson kind. They…

Numerical Analysis · Mathematics 2026-01-05 Alexander Zlotnik , Ilya Zlotnik

We report experimental implementation of discrete Fourier transformation(DFT) on a nuclear magnetic resonance(NMR) quantum computer. Experimental results agree with theoretical results. Using the pulse sequences we introduced, DFT can be…

Quantum Physics · Physics 2007-05-23 Liping Fu , Jun Luo , Li Xiao , Xizhi Zeng

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

A wavelength-tunable Optical Fiber Tweezer (OFT) based on a Graded Index Multimode Fiber (GIMF) with a flat endface is proposed. It is shown that the design can support a trapping position which is far from the tip of the GIMF compared with…

Optics · Physics 2017-10-11 Esmaeil Mobini , Arash Mafi

Background: Windowed Fourier decompositions (WFD) are widely used in measuring stationary and non-stationary spectral phenomena and in describing pairwise relationships among multiple signals. Although a variety of WFDs see frequent…

Quantitative Methods · Quantitative Biology 2019-01-30 Christopher K. Kovach , Phillip E. Gander

In this paper, we introduce a low-complexity approximation for the discrete Tchebichef transform (DTT). The proposed forward and inverse transforms are multiplication-free and require a reduced number of additions and bit-shifting…

Methodology · Statistics 2015-02-03 P. A. M. Oliveira , R. J. Cintra , F. M. Bayer , S. Kulasekera , A. Madanayake

Fourier transform (FT) plays a crucial role in a broad range of applications, from enhancement, restoration and analysis through to security, compression and manipulation. The Fourier transform (FT) is a process that converts a function…

Numerical Analysis · Mathematics 2023-05-05 Benjamin Kenwright

In this proceeding contribution, we review a recently proposed method to compute the minimal form factors (MFFs) of diagonal integrable field theories perturbed by irrelevant fields of the $T\bar{T}$ family. Our construction generalizes…

High Energy Physics - Theory · Physics 2025-11-18 Olalla A. Castro-Alvaredo , Stefano Negro , Fabio Sailis

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

Truncated Fourier Transforms (TFTs), first introduced by Van der Hoeven, refer to a family of algorithms that attempt to smooth "jumps" in complexity exhibited by FFT algorithms. We present an in-place TFT whose time complexity, measured in…

Symbolic Computation · Computer Science 2013-01-30 Andrew Arnold

This paper describes and compares some structure preserving techniques for the solution of linear discrete ill-posed problems with the t-product. A new randomized tensor singular value decomposition (R-tSVD) with a t-product is presented…

Numerical Analysis · Mathematics 2021-10-18 Ugochukwu O. Ugwu , Lothar Reichel
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