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  • Chavan, Tanmay; Dutta, Sangya; Mohapatra, Nihar Ranjan; Ganguly, Udayan (Institute of Electrical and Electronics Engineers, 2020-06)
    The human brain comprises about a hundred billion neurons connected through quadrillion synapses. Spiking neural networks (SNNs) take inspiration from the brain to model complex cognitive and learning tasks. Neuromorphic ...
  • Dutta, Sangya; Chavan, Tanmay; Shukla, S.; Kumar, V.; Shukla, A.; Mohapatra, Nihar Ranjan; Ganguly, Udayan (Cambridge University Press, 2018-06)
    Spiking Neural Networks propose to mimic nature’s way of recognizing patterns and making decisions in a fuzzy manner. To develop such networks in hardware, a highly manufacturable technology is required. We have proposed ...
  • Dutta, Sangya; Chavan, Tanmay; Mohapatra, Nihar Ranjan; Ganguly, Udayan (Elsevier, 2013-10)
    The hardware realization of spiking neural network (SNN) requires a compact and energy efficient electronic analog to the biological neuron. A knob to tune the response of the as-fabricated neuron allows the network to ...
  • Dutta, Sangya; Kumar, Vinay; Shukla, Aditya; Mohapatra, Nihar Ranjan; Ganguly, Udayan (Nature Publishing Group, 2017-12)
    Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, ...
  • Dutta, Sangya; Bhattacharya, Tinish; Mohapatra, Nihar Ranjan; Suri,Manan; Ganguly, Udayan (IEEE, 2018-10)
    Variability is an integral part of biology. A biological neural network performs efficiently despite variability and sometimes its performance is facilitated by the variability. Hence, the study of variability on its ...

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