Ieee Signal Processing Magazine投稿须知

期刊简介

《Ieee Signal Processing Magazine》是由Institute of Electrical and Electronics Engineers Inc.出版社于1984年创办的英文国际期刊（ISSN: 1053-5888，E-ISSN: 1558-0792），该期刊长期致力于工程：电子与电气领域的创新研究，主要研究方向为工程技术-工程：电子与电气。作为SCIE收录期刊（JCR分区 Q1，中科院 1区），本刊采用OA未开放获取模式（OA占比0%），以发表工程：电子与电气领域等方向的原创性研究为核心（研究类文章占比100.00%%）。凭借严格的同行评审与高效编辑流程，期刊年载文量精选控制在86篇，确保学术质量与前沿性。成果覆盖Web of Science、Scopus等国际权威数据库，为学者提供推动工程技术领域高水平交流平台。

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Ieee Signal Processing Magazine审稿周期约为较慢,6-12周。该刊近年未被列入国际预警名单，年发文量约86篇，录用竞争适中，主题需确保紧密契合工程技术前沿。投稿策略提示：避开学术会议旺季投稿以缩短周期，语言建议专业润色提升可读性。

工程技术 大类学科
English 出版语言
否是否预警
SCIE 期刊收录
86 发文量

中科院分区

中科院 SCI 期刊分区 2023年12月升级版

Top期刊	综述期刊	大类学科	小类学科
否	否	工程技术 1区	ENGINEERING, ELECTRICAL & ELECTRONIC 工程：电子与电气 2区

中科院 SCI 期刊分区 2022年12月升级版

Top期刊	综述期刊	大类学科	小类学科
是	否	工程技术 1区	ENGINEERING, ELECTRICAL & ELECTRONIC 工程：电子与电气 1区

JCR分区

按JIF指标学科分区	收录子集	分区	排名	百分位
学科：ENGINEERING, ELECTRICAL & ELECTRONIC	SCIE	Q1	12 / 352	96.7%

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：ENGINEERING, ELECTRICAL & ELECTRONIC	SCIE	Q1	5 / 354	98.73%

CiteScore

SJR

SNIP

CiteScore 排名

CiteScore：27.2

SJR：4.896

SNIP：5.469

学科类别	分区	排名	百分位
大类：Mathematics 小类：Applied Mathematics	Q1	2 / 635	99%
大类：Mathematics 小类：Electrical and Electronic Engineering	Q1	8 / 797	99%
大类：Mathematics 小类：Signal Processing	Q1	2 / 131	98%

期刊发文

Physics-Inspired Compressive Sensing: Beyond deep unrolling
Author: Zhang, Jian; Chen, Bin; Xiong, Ruiqin; Zhang, Yongbing

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 1, pp. 58-72. DOI: 10.1109/MSP.2022.3208394
Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing: Nonlocal sparse and low-rank modeling
Author: Zha, Zhiyuan; Wen, Bihan; Yuan, Xin; Ravishankar, Saiprasad; Zhou, Jiantao; Zhu, Ce

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 1, pp. 32-44. DOI: 10.1109/MSP.2022.3217936
Bayesian Deep Learning for Image Reconstruction: From structured sparsity to uncertainty estimation
Author: Dong, Weisheng; Wu, Jinjian; Li, Leida; Shi, Guangming; Li, Xin

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 1, pp. 73-84. DOI: 10.1109/MSP.2022.3176421
Physics-Driven Deep Learning Methods for Fast Quantitative Magnetic Resonance Imaging: Performance improvements through integration with deep neural networks
Author: Zhu, Yanjie; Cheng, Jing; Cui, Zhuo-Xu; Zhu, Qingyong; Ying, Leslie; Liang, Dong

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 2, pp. 116-128. DOI: 10.1109/MSP.2023.3236483
Physics-Driven Synthetic Data Learning for Biomedical Magnetic Resonance: The imaging physics-based data synthesis paradigm for artificial intelligence
Author: Yang, Qinqin; Wang, Zi; Guo, Kunyuan; Cai, Congbo; Qu, Xiaobo

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 2, pp. 129-140. DOI: 10.1109/MSP.2022.3183809
Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey
Author: Xia, Wenjun; Shan, Hongming; Wang, Ge; Zhang, Yi

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 2, pp. 89-100. DOI: 10.1109/MSP.2022.3204407
High-Dimensional MR Spatiospectral Imaging by Integrating Physics-Based Modeling and Data-Driven Machine Learning: Current progress and future directions
Author: Lam, Fan; Peng, Xi; Liang, Zhi-Pei

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 2, pp. 101-115. DOI: 10.1109/MSP.2022.3203867
Physics-Embedded Machine Learning for Electromagnetic Data Imaging: Examining three types of data-driven imaging methods
Author: Guo, Rui; Huang, Tianyao; Li, Maokun; Zhang, Haiyang; Eldar, Yonina C.

Journal: IEEE SIGNAL PROCESSING MAGAZINE. 2023; Vol. 40, Issue 2, pp. 18-31. DOI: 10.1109/MSP.2022.3198805

Ieee Signal Processing Magazine

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