SVE-Former: A fast fourier transformer via singular vector embedding.

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Bibliographic Details
Title: SVE-Former: A fast fourier transformer via singular vector embedding.
Authors: Shen XJ; School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu University Campus, Zhenjiang, 212013, Jiangsu, China., Tian W; School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu University Campus, Zhenjiang, 212013, Jiangsu, China., Yang Y; School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu University Campus, Zhenjiang, 212013, Jiangsu, China., Zhou C; School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu University Campus, Zhenjiang, 212013, Jiangsu, China., Song H; School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu University Campus, Zhenjiang, 212013, Jiangsu, China., Yang M; College of Mathematical Sciences, Harbin Engineering University, Harbin Engineering University, Harbin, 150001, Heilongjiang, China., Li Y; Nanjing Les Information Technology Co., Ltd, Nanjing Les Information Technology Co., Ltd, Nanjing, 210001, Jiangsu, China., Tian S; School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, China. Electronic address: tiansirui@njust.edu.cn., Zha Z; University of Science and Technology of China (USTC), USTC, Hefei, 230011, Anhui, China.
Source: Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2026 Apr; Vol. 196, pp. 108331. Date of Electronic Publication: 2025 Nov 19.
Publication Type: Journal Article
Journal Info: Publisher: Pergamon Press Country of Publication: United States NLM ID: 8805018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2782 (Electronic) Linking ISSN: 08936080 NLM ISO Abbreviation: Neural Netw Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-2782
DOI:10.1016/j.neunet.2025.108331