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eess.SY2025
Bellman Memory Units: A neuromorphic framework for synaptic reinforcement learning with an evolving network topology
Shreyan Banerjee, Aasifa Rounak, Vikram Pakrashi
Application of neuromorphic edge devices for control is limited by the constraints on gradient-free online learning and scalability of the hardware across control problems. This pa…
eess.SY2025
Benchmarking Spiking Neurons for Linear Quadratic Regulator Control of Multi-linked Pole on a Cart: from Single Neuron to Ensemble
Shreyan Banerjee, Luna Gava, Aasifa Rounak +1
The emerging field of neuromorphic computing for edge control applications poses the need to quantitatively estimate and limit the number of spiking neurons, to reduce network comp…