@inproceedings{18ec1ef8f5d74658bc7427ef479a5701,
title = "Arithmetic computing via rate coding in neural circuits with spike-triggered adaptive synapses",
abstract = "We present spiking neural circuits with spike-time dependent adaptive synapses capable of performing a variety of basic mathematical computations. These circuits encode and process information in the spike rates that lie between 40-140 Hz. The synapses in our circuit obey simple, local and spike-time dependent adaptation rules. We demonstrate that our circuits can perform the fundamental operations - addition, subtraction, multiplication and division, as well as other non-linear transformations such as exponentiation and logarithm for time dependent signals in real-time. We show that our spiking neural circuits are tolerant to a high degree of noise in the input variables, and illustrate its computational capability in an exemplary signal estimation problem. Our circuits can thus be used in a wide variety of hardware and software implementations for navigation, control and computation.",
keywords = "Estimation, MATLAB, Neurons",
author = "Sushrut Thorat and Bipin Rajendran",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Joint Conference on Neural Networks, IJCNN 2015 ; Conference date: 12-07-2015 Through 17-07-2015",
year = "2015",
month = sep,
day = "28",
doi = "10.1109/IJCNN.2015.7280822",
language = "English (US)",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 International Joint Conference on Neural Networks, IJCNN 2015",
address = "United States",
}