Spiking Sparse Recovery With Non-Convex Penalties
Author:
Affiliation:
1. School of Electronic and Information, Wuhan University, Wuhan, China
2. INRIA Lille Villeneuve d'Ascq, Villeneuve d'Ascq, France
3. Weizmann Institute of Science, Rehovot, Israel
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hubei Province, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/78/9675017/10007054.pdf?arnumber=10007054
Reference46 articles.
1. The Convergence Guarantees of a Non-Convex Approach for Sparse Recovery
2. Towards artificial general intelligence with hybrid Tianjic chip architecture
3. Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook
4. A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)
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