10 citations · 12 across the 5 of their papers we have counts for
5 papers
DendroNN: Dendrocentric Neural Networks for Energy-Efficient Classification of Event-Based Data
Jann Krausse, Zhe Su, Kyrus Mama +4
Spatiotemporal information is at the core of diverse sensory processing and computational tasks. Feed-forward spiking neural networks can be used to solve these tasks while offerin…
A Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures
Fernando M. Quintana, Maryada, Pedro L. Galindo +3
Developing dedicated mixed-signal neuromorphic computing systems optimized for real-time sensory-processing in extreme edge-computing applications requires time-consuming design, f…
Gradient-descent hardware-aware training and deployment for mixed-signal Neuromorphic processors
Uğurcan Çakal, Maryada, Chenxi Wu +2
Mixed-signal neuromorphic processors provide extremely low-power operation for edge inference workloads, taking advantage of sparse asynchronous computation within Spiking Neural N…
Neuromorphic implementation of ECG anomaly detection using delay chains
Stefan Gerber, Marc Steiner, Maryada +2
Real-time analysis and classification of bio-signals measured using wearable devices is computationally costly and requires dedicated low-power hardware. One promising approach is…
Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm
A. Linares-Barranco, E. Pinero-Fuentes, S. Canas-Moreno +6
Biological nervous systems typically perform the control of numerous degrees of freedom for example in animal limbs. Neuromorphic engineers study these systems by emulating them in…