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Neural Processing Letters

Publishing model:
Open access

Overview

Neural Processing Letters is an international journal that promotes fast exchange of the current state-of-the art contributions among the artificial neural network community of researchers and users. The Journal publishes technical articles on various aspects of artificial neural networks and machine learning systems. Coverage includes novel architectures, supervised and unsupervised learning algorithms, deep nets, learning theory, network dynamics, self-organization, optimization, biological neural network modelling, and hybrid neural/fuzzy logic/genetic systems. The Journal publishes articles on methodological innovations for the applications of the aforementioned systems in classification, pattern recognition, signal processing, image and video processing, robotics, control, autonomous vehicles, financial forecasting, big data analytics, and other multidisciplinary applications.

Editors-in-Chief
  • Michel Verleysen,
  • Mohamad H. Hassoun
Journal Impact Factor
2.6 (2023)
5-year Journal Impact Factor
2.4 (2023)
Submission to first decision (median)
3 days
Downloads
340,520 (2023)

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Journal information

Electronic ISSN
1573-773X
Print ISSN
1370-4621
Abstracted and indexed in
  1. ACM Digital Library
  2. ANVUR
  3. BFI List
  4. Baidu
  5. CLOCKSS
  6. CNKI
  7. CNPIEC
  8. DBLP
  9. Dimensions
  10. EBSCO
  11. EI Compendex
  12. Google Scholar
  13. INSPEC
  14. Japanese Science and Technology Agency (JST)
  15. Naver
  16. OCLC WorldCat Discovery Service
  17. Portico
  18. ProQuest
  19. SCImago
  20. SCOPUS
  21. Science Citation Index Expanded (SCIE)
  22. TD Net Discovery Service
  23. UGC-CARE List (India)
  24. Wanfang
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