Guest Editorial Dynamical Neuro-AI Learning Systems: Devices, Circuits, Architecture and Algorithms

This Special Issue of IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) is dedicated to demonstrating the latest research progress on dynamical neuro-artificial intelligence (AI) learning systems that bridge the gap between devices, circuits, architectures, and algorithms...

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Veröffentlicht in:IEEE journal on emerging and selected topics in circuits and systems Jg. 13; H. 4; S. 873 - 876
Hauptverfasser: Eshraghian, Jason K., Basu, Arindam, Lammie, Corey, Liu, Shih-Chii, Panda, Priydarshini
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.12.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithm design and theory
Algorithms
Artificial intelligence
Circuits
Deep learning
Learning systems
Machine learning
Neural engineering
Special issues and sections
ISSN:2156-3357, 2156-3365
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:This Special Issue of IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) is dedicated to demonstrating the latest research progress on dynamical neuro-artificial intelligence (AI) learning systems that bridge the gap between devices, circuits, architectures, and algorithms. The growing demand for AI has spurred the development of systems that: 1) co-localize computation and memory; 2) enhance circuits and devices optimized for operations prevalent in deep learning; and 3) implement lightweight and compressed machine learning models thereby achieving greater accuracy with less resources.
Bibliographie:SourceType-Scholarly Journals-1
content type line 14
ObjectType-Editorial-2
ObjectType-Commentary-1
ISSN:2156-3357
2156-3365
DOI:10.1109/JETCAS.2023.3343932