24 citations · 26 across the 5 of their papers we have counts for
5 papers
Learning in Feedback-driven Recurrent Spiking Neural Networks using full-FORCE Training
Ankita Paul, Stefan Wagner, Anup Das
Feedback-driven recurrent spiking neural networks (RSNNs) are powerful computational models that can mimic dynamical systems. However, the presence of a feedback loop from the read…
A Design Methodology for Fault-Tolerant Computing using Astrocyte Neural Networks
Murat Işık, Ankita Paul, M. Lakshmi Varshika +1
We propose a design methodology to facilitate fault tolerance of deep learning models. First, we implement a many-core fault-tolerant neuromorphic hardware design, where neuron and…
Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants
Ankita Paul, Md. Abu Saleh Tajin, Anup Das +2
Precise monitoring of respiratory rate in premature infants is essential to initiate medical interventions as required. Wired technologies can be invasive and obtrusive to the pati…
Implementing Spiking Neural Networks on Neuromorphic Architectures: A Review
Phu Khanh Huynh, M. Lakshmi Varshika, Ankita Paul +3
Recently, both industry and academia have proposed several different neuromorphic systems to execute machine learning applications that are designed using Spiking Neural Networks (…
On the Mitigation of Read Disturbances in Neuromorphic Inference Hardware
Ankita Paul, Shihao Song, Twisha Titirsha +1
Non-Volatile Memory (NVM) cells are used in neuromorphic hardware to store model parameters, which are programmed as resistance states. NVMs suffer from the read disturb issue, whe…