Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks

Authors

  • Lakshay Sahni Delhi Technical University
  • Debasrita Chakraborty Indian Statistical Institute
  • Ashish Ghosh Indian Statistical Institute

DOI:

https://doi.org/10.1609/aaai.v33i01.330110021

Abstract

Latest developments in the field of power-efficient neural interface circuits provide an excellent platform for applications where power consumption is the primary concern. Developing neural networks to achieve pattern recognition on such hardware remains a daunting task owing to substantial computational complexity. We propose and demonstrate a Spiking Neural Network (SNN) with biologically reasonable time constants to implement basic Boolean Logic Gates. The same network can be further applied to more complex problem statements. We employ a frequency spike encoding for data representation in the model, and a simplified and computationally efficient model of a neuron with exponential synapses and Spike Timing Dependent Plasticity (STDP).

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Published

2019-07-17

How to Cite

Sahni, L., Chakraborty, D., & Ghosh, A. (2019). Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 10021-10022. https://doi.org/10.1609/aaai.v33i01.330110021

Issue

Section

Student Abstract Track