LALI, M Selim-Antoine (2024) Spiking Recurrent Neural Network with Feedback Control PRE - Research Project, ENSTA.
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Abstract
The primary objective of this project was to explore the implementation of SRNNs incorporating feedback control mechanisms. Specifically, I investigated how biologically realistic feedback control, through gain and shift modulation, can enhance the performance of SRNNs in generating target outputs.
Item Type: | Thesis (PRE - Research Project) |
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Uncontrolled Keywords: | Spiking Recurrent Neural Networks, Neural Circuit Dynamics, Feedback Control, Gain Modulation, Hebbian Learning, Synaptic Plasticity, Leaky Integrate-and-Fire Model, Surrogate Gradient, Computational Neuroscience, Python programming language |
Subjects: | Mathematics and Applications |
ID Code: | 10158 |
Deposited By: | Selim-antoine LALI |
Deposited On: | 27 août 2024 18:11 |
Dernière modification: | 02 sept. 2024 16:19 |
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