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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

The matrix expressions for every parts of a transformer are firstly described. Based on semi-tensor product (STP) of matrices the hypervectors are reconsidered and the linear transformation over hypervectors is constructed by using…

Machine Learning · Computer Science 2025-04-22 Daizhan Cheng

The quadratic phase Fourier transform (QPFT) is a generalization of several well-known integral transforms, including the linear canonical transform (LCT), fractional Fourier transform (FrFT), and Fourier transform (FT). This paper…

Functional Analysis · Mathematics 2025-05-06 Sarga Varghese , Gita Rani Mahato , Manab Kundu

Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank matrices $A$ and $B$ to represent the weight change, i.e.,…

Machine Learning · Computer Science 2024-05-07 Ziqi Gao , Qichao Wang , Aochuan Chen , Zijing Liu , Bingzhe Wu , Liang Chen , Jia Li

The efficient multiangle centered discrete fractional Fourier transform (MA-CDFRFT) [1] has proven to be a useful tool for time-frequency analysis; in this paper, we generalize the MA-CDFRFT to general M -periodic transforms, which, among…

Signal Processing · Electrical Eng. & Systems 2026-05-01 Christian Oswald , Franz Pernkopf

In this paper we demonstrate the methodology for parallelizing the computation of large one-dimensional discrete fast Fourier transforms (DFFTs) on multi-core Intel Xeon processors. DFFTs based on the recursive Cooley-Tukey method have to…

Mathematical Software · Computer Science 2016-07-12 Ryo Asai , Andrey Vladimirov

Nonequispaced discrete Fourier transformation (NDFT) is widely applied in all aspects of computational science and engineering. The computational efficiency and accuracy of NDFT has always been a critical issue in hindering its…

Mathematical Software · Computer Science 2020-08-06 Sheng-Chun Yang , Yong-Lei Wang

Mechanistic interpretability seeks to understand how Large Language Models (LLMs) represent and process information. Recent approaches based on dictionary learning and transcoders enable representing model computation in terms of sparse,…

Multivariate time series forecasting is a pivotal task in several domains, including financial planning, medical diagnostics, and climate science. This paper presents the Neural Fourier Transform (NFT) algorithm, which combines…

Machine Learning · Computer Science 2024-05-24 Noam Koren , Kira Radinsky

Large-scale cross-lingual language models (LM), such as mBERT, Unicoder and XLM, have achieved great success in cross-lingual representation learning. However, when applied to zero-shot cross-lingual transfer tasks, most existing methods…

Computation and Language · Computer Science 2020-12-16 Yuwei Fang , Shuohang Wang , Zhe Gan , Siqi Sun , Jingjing Liu

The $N$-point discrete Fourier transform (DFT) is a cornerstone for several signal processing applications. Many of these applications operate in real-time, making the computational complexity of the DFT a critical performance indicator to…

Data Structures and Algorithms · Computer Science 2024-12-18 Saulo Queiroz , João P. Vilela , Edmundo Monteiro

Electronic structure calculations based on density-functional theory (DFT) represent a significant part of today's HPC workloads and pose high demands on high-performance computing resources. To perform these quantum-mechanical DFT…

Computational Physics · Physics 2021-04-28 Michael Lass , Robert Schade , Thomas D. Kühne , Christian Plessl

The scaling of large language models (LLMs) is currently bottlenecked by the rigidity of distributed programming. While high-performance libraries like CuBLAS and NCCL provide optimized primitives, they lack the flexibility required for…

Transform Dialect in MLIR provides operations that can be used to control transformation of the Intermediate Representation (IR) using a different portion of the IR. It refers to the IR being transformed as payload IR, and to the IR guiding…

Programming Languages · Computer Science 2024-05-01 Oleksandr Zinenko

Multi-Level Intermediate Representation (MLIR) is a novel compiler infrastructure that aims to provide modular and extensible components to facilitate building domain specific compilers. However, since MLIR models programs at an…

Programming Languages · Computer Science 2023-08-15 Maksim Levental , Alok Kamatar , Ryan Chard , Kyle Chard , Ian Foster

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…

In this letter, a fast Fourier transform (FFT)-enhanced low-complexity super-resolution sensing algorithm for near-field source localization with both angle and range estimation is proposed. Most traditional near-field source localization…

Signal Processing · Electrical Eng. & Systems 2024-11-26 Yuxiao Wu , Huizhi Wang , Yong Zeng

A new transform over finite fields, the finite field Hartley transform (FFHT), was recently introduced and a number of promising applications on the design of efficient multiple access systems and multilevel spread spectrum sequences were…

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

The fast Fourier transform (FFT) is a primitive kernel in numerous fields of science and engineering. OpenFFT is an open-source parallel package for 3-D FFTs, built on a communication-optimal domain decomposition method for achieving…

Mathematical Software · Computer Science 2015-08-27 Truong Vinh Truong Duy , Taisuke Ozaki

Freely Long-Thinking Transformer (FraiLT) is an improved transformer model designed to enhance processing capabilities without scaling up size. It utilizes a recursive approach, iterating over a subset of layers multiple times, and…

Machine Learning · Computer Science 2024-02-27 Akbay Tabak
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