Inspired by biological neural systems, neuromorphic computing has drawn much attention for its great potential of achieving machine intelligence at extremely low energy dissipation. Bio-inspired computing models have been investigated for information encoding, sparse representation, event-driven communication/computation, and online learning. This new computing paradigm triggered a recent wave of innovations in software and hardware architecture and emerging device technology, which consequently enabled many novel applications. This is an exemplar research area where the application, computing model, architecture, and circuit-level design are closely coupled to deliver unprecedented functionality and energy efficiency.
This special issue of IEEE Transactions on Computers will explore academic and industrial research on all topics related to neuromorphic computing, from computing model, software, and hardware architecture to application design. Topics of interest to this special issue include, but not limited to:
- Network, neuron, and synapse models of bio-inspired and spiking neural networks
- Non-von Neumann computing architectures
- Emerging devices and hardware implementations
- Supervised or unsupervised learning in neuromorphic computing systems
- Biologically inspired network structure and computing models
- Applications where neuromorphic systems have the potential to outperform state-of-the-art techniques
- Online learning and real-time applications of neuromorphic systems
- Application, computing model, and hardware architecture co-design for neuromorphic systems
Important Dates
Submission Deadline: 1 November 2021
Reviews Completed: December 15, 2021
Major Revisions Due: February 1, 2022
Reviews of Revisions Completed: March 15, 2022
Notification of Final Acceptance: April 15, 2022
Publication Materials for Final Manuscripts Due: May 1, 2022
Publication: July 2022
Submission Guidelines
Submitted papers must include new significant research-based technical contributions in the scope of the journal. Papers under review elsewhere are not acceptable for submission. Extended versions of published conference papers (to be included as part of the submission together with a summary of differences) are welcome, but there must be at least 30% new impacting technical/scientific material in the submitted journal version, and there should be less than 50% verbatim similarity level as reported by a tool (such as CrossRef). Guidelines concerning the submission process and LaTeX and Word templates can be found on the Author Information webpage. While submitting through ScholarOne, please select this special-issue option. As per TC policies, only full-length papers (12 pages) can be submitted to special issues, and each author’s bio should not exceed 150 words.
Questions?
Please address all correspondence regarding this special issue to Lead Guest Editor Yiran Chen at yiran.chen@duke.edu.
Guest Editors
Yiran Chen
Department of Electrical & Computer Engineering
Duke University
Qinru Qiu
Department of Electrical Engineering & Computer Science
Syracuse University
Corresponding Topical Editor
James Hoe
Department of Electrical and Computer Engineering
Carnegie Mellon University
