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Multiplierless Digital Implementation of Time-Varying FitzHugh–Nagumo Model.
- Source :
-
IEEE Transactions on Circuits & Systems. Part I: Regular Papers . Jul2019, Vol. 66 Issue 7, p2662-2670. 9p. - Publication Year :
- 2019
-
Abstract
- Low-cost accurate digital realization of the spiking neural networks is crucial to investigate the behaviors of human brain performance. This paper presents a multiplierless burst-mode Fitz–Hugh Nagumo (MBM-FHN) model, which is used for generating the burst-mode of the FHN neuron model. Using extra parameters (time-varying function) in neuron equations and estimating it by linear function, efficient low-cost and high-speed implementation is achieved. The simulation results show that the MBM-FHN model generates the similar bursting patterns of the original FHN neuron. The comparison shows that the MBM-FHN model has a better performance and best cost reduction related to the original neuron model especially in overall saving and speed-up parameters. [ABSTRACT FROM AUTHOR]
- Subjects :
- *FIELD programmable gate arrays
*LINEAR equations
Subjects
Details
- Language :
- English
- ISSN :
- 15498328
- Volume :
- 66
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Circuits & Systems. Part I: Regular Papers
- Publication Type :
- Periodical
- Accession number :
- 137116457
- Full Text :
- https://doi.org/10.1109/TCSI.2019.2899361