@inproceedings{7ef31235554242268cf640c6fcc85a5d,
title = "Programmable memristor emulator ASIC for biologically inspired memristive learning",
abstract = "This paper details a fully programmable floating memristor (resistor with memory) emulator ASIC designed for biologically inspired memristive learning. Since real memristor is not commercially available, a compact memristor emulator is needed for device study. The designed ASIC has a memristor emulator with conductance range from 4.88nS to 4.99μS (200KΩ to 204.8MΩ). The memristor emulator is a switchedresistor based circuit with processing performed off-chip in a FPGA. The processing has been planned to be off-chip to get the freedom of programmability of any function. This paper explains the memristor emulator and the realization of synapse functionality used in neuromorphic circuits like long term potentiation (LTP), Long Term depression (LTD) and synaptic plasticity. The ASIC has been designed and fabricated in AMS 350nm process.",
keywords = "ASIC, Emulator, LTD, LTP, Memristor, Neuron, Synaptic plasticity",
author = "Rajeev Ranjan and Ponce, {Pablo Mendoza} and Anirudh Kankuppe and Bibin John and Saleh, {Lait Abu} and Dietmar Schroeder and Krautschneider, {Wolfgang H.}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 39th International Conference on Telecommunications and Signal Processing, TSP 2016 ; Conference date: 27-06-2016 Through 29-06-2016",
year = "2016",
month = nov,
day = "28",
doi = "10.1109/TSP.2016.7760874",
language = "Ingl{\'e}s",
series = "2016 39th International Conference on Telecommunications and Signal Processing, TSP 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "261--264",
editor = "Norbert Herencsar",
booktitle = "2016 39th International Conference on Telecommunications and Signal Processing, TSP 2016",
}