TY - GEN
T1 - Modelling of nanowire FETs based neural network for tactile pattern recognition in E-skin
AU - Taube, William
AU - Liu, Fengyuan
AU - Vilouras, Anastasios
AU - Shaktivel, Dhayalan
AU - Nunez, Carlos Garcia
AU - Heidari, Hadi
AU - Labeau, Fabrice
AU - Gregory, Duncan
AU - Dahiya, Ravinder
PY - 2016/1/1
Y1 - 2016/1/1
N2 - This paper presents device, circuit and system modelling to validate the use of neural nanowire FETs (u-NWFETs) towards a hardware-realizable Neural Network. Hardware neural networks are promising for neuromorphic computing and have many prospective applications for bi-directional interface in prosthetics, and electroceuticals etc. Device simulation of a u-NWFET has been carried out followed by circuit implementation to validate the use of silicon nanowires (Si-NWs) as neuronal elements. A system level simulation of 258 neurons (225 sensor neurons, 50 hidden layer neurons and 3 output layer neurons) has been performed to demonstrate tactile pattern recognition. Training has been carried out and validation of the trained network gives an accurate classification of a database of 50 tactile images into 3 classifiers.
AB - This paper presents device, circuit and system modelling to validate the use of neural nanowire FETs (u-NWFETs) towards a hardware-realizable Neural Network. Hardware neural networks are promising for neuromorphic computing and have many prospective applications for bi-directional interface in prosthetics, and electroceuticals etc. Device simulation of a u-NWFET has been carried out followed by circuit implementation to validate the use of silicon nanowires (Si-NWs) as neuronal elements. A system level simulation of 258 neurons (225 sensor neurons, 50 hidden layer neurons and 3 output layer neurons) has been performed to demonstrate tactile pattern recognition. Training has been carried out and validation of the trained network gives an accurate classification of a database of 50 tactile images into 3 classifiers.
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U2 - 10.1109/BioCAS.2016.7833859
DO - 10.1109/BioCAS.2016.7833859
M3 - Conference contribution
AN - SCOPUS:85014178284
T3 - Proceedings - 2016 IEEE Biomedical Circuits and Systems Conference, BioCAS 2016
SP - 572
EP - 575
BT - Proceedings - 2016 IEEE Biomedical Circuits and Systems Conference, BioCAS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE Biomedical Circuits and Systems Conference, BioCAS 2016
Y2 - 17 October 2016 through 19 October 2016
ER -