2 citations · 8 across the 5 of their papers we have counts for
5 papers
Hardware-friendly Neural Network Architecture for Neuromorphic Computing
Roshan Gopalakrishnan, Yansong Chua, Ashish Jith Sreejith Kumar
The hardware-software co-optimization of neural network architectures is becoming a major stream of research especially due to the emergence of commercial neuromorphic chips such a…
RRAM based neuromorphic algorithms
Roshan Gopalakrishnan
This submission is a report on RRAM based neuromorphic algorithms. This report basically gives an overview of the algorithms implemented on neuromorphic hardware with crossbar arra…
MaD: Mapping and debugging framework for implementing deep neural network onto a neuromorphic chip with crossbar array of synapses
Roshan Gopalakrishnan, Ashish Jith Sreejith Kumar, Yansong Chua
Neuromorphic systems or dedicated hardware for neuromorphic computing is getting popular with the advancement in research on different device materials for synapses, especially in…
Classifying neuromorphic data using a deep learning framework for image classification
Roshan Gopalakrishnan, Yansong Chua, Laxmi R Iyer
In the field of artificial intelligence, neuromorphic computing has been around for several decades. Deep learning has however made much recent progress such that it consistently o…
Triplet Spike Time Dependent Plasticity: A floating-gate Implementation
Roshan Gopalakrishnan, Arindam Basu
Synapse plays an important role of learning in a neural network; the learning rules which modify the synaptic strength based on the timing difference between the pre- and post-syna…