Efficient Neuromorphic Signal Processing with Resonator Neurons
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Published:2022-05-26
Issue:10
Volume:94
Page:917-927
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ISSN:1939-8018
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Container-title:Journal of Signal Processing Systems
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language:en
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Short-container-title:J Sign Process Syst
Author:
Frady E. PaxonORCID, Sanborn Sophia, Shrestha Sumit Bam, Rubin Daniel Ben Dayan, Orchard Garrick, Sommer Friedrich T., Davies Mike
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Modeling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering
Reference22 articles.
1. Davies, M., Srinivasa, N., Lin, T., Chinya, G., Cao, Y., Choday, S. H., Dimou, G., Joshi, P., Imam, N., Jain, S., Liao, Y., Lin, C., Lines, A., Liu, R., Mathaikutty, D., McCoy, S., Paul, A., Tse, J., Venkataramanan, G., Weng, Y., Wild, A., Yang, Y., & Wang, H. (2018). Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro, 38(1), 82–99. 2. Davies, M., Wild, A., Orchard, G., Sandamirskaya, Y., Guerra, G. A. F., Joshi, P., Plank, P., & Risbud, S. R. (2021). Advancing neuromorphic computing with Loihi: A survey of results and outlook. Proceedings of the IEEE, 109(5), 911–934. 3. Arthur, J. V., & Boahen, K. A. (2010). Silicon-neuron design: A dynamical systems approach. IEEE Transactions on Circuits and Systems I, 58(5), 1034–1043. 4. Frady, E. P., & Sommer, F. T. (2019). Robust computation with rhythmic spike patterns. PNAS, 116(36), 18050–18059. 5. Polikar, R. (1996). Fundamental concepts & an overview of the wavelet theory.
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