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Characterisation and modelling of Mg doped ZnO TFTs

Published in In the proceedings of 2015 11th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME), 2015

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Recommended citation: A. Shaw, C. Gao, J. Jin, I. Mitrovic, S. Hall, "Characterisation and modelling of Mg doped ZnO TFTs." In the proceedings of 2015 11th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME), 2015.

On-chip ID generation for multi-node implantable devices using SA-PUF

Published in In the proceedings of 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017

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Recommended citation: Chang Gao, Sara Ghoreishizadeh, Yan Liu, Timothy Constandinou, "On-chip ID generation for multi-node implantable devices using SA-PUF." In the proceedings of 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017.

DeltaRNN: A Power-Efficient Recurrent Neural Network Accelerator

Published in In the proceedings of Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018

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Recommended citation: Chang Gao, Daniel Neil, Enea Ceolini, Shih-Chii Liu, Tobi Delbruck, "DeltaRNN: A Power-Efficient Recurrent Neural Network Accelerator." In the proceedings of Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018. https://doi.org/10.1145/3174243.3174261

Live Demonstration: Real-Time Spoken Digit Recognition using the DeltaRNN Accelerator

Published in In the proceedings of 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019

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Recommended citation: Chang Gao, Stefan Braun, Ilya Kiselev, Jithendar Anumula, Tobi Delbruck, Shih-Chii Liu, "Live Demonstration: Real-Time Spoken Digit Recognition using the DeltaRNN Accelerator." In the proceedings of 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019.

Real-Time Speech Recognition for IoT Purpose using a Delta Recurrent Neural Network Accelerator

Published in In the proceedings of 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019

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Recommended citation: Chang Gao, Stefan Braun, Ilya Kiselev, Jithendar Anumula, Tobi Delbruck, Shih-Chii Liu, "Real-Time Speech Recognition for IoT Purpose using a Delta Recurrent Neural Network Accelerator." In the proceedings of 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019.

EdgeDRNN: Enabling Low-latency Recurrent Neural Network Edge Inference

Published in In the proceedings of 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020

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Recommended citation: Chang Gao, Antonio Rios-Navarro, Xi Chen, Tobi Delbruck, Shih-Chii Liu, "EdgeDRNN: Enabling Low-latency Recurrent Neural Network Edge Inference." In the proceedings of 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020.

EdgeDRNN: Recurrent Neural Network Accelerator for Edge Inference

Published in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2020

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Recommended citation: Chang Gao, Antonio Rios-Navarro, Xi Chen, Shih-Chii Liu, Tobi Delbruck, "EdgeDRNN: Recurrent Neural Network Accelerator for Edge Inference." IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2020.

Recurrent Neural Network Control of a Hybrid Dynamical Transfemoral Prosthesis with EdgeDRNN Accelerator

Published in In the proceedings of 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020

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Recommended citation: Chang Gao*, Rachel Gehlhar*, Aaron Ames, Shih-Chii Liu, Tobi Delbruck, "Recurrent Neural Network Control of a Hybrid Dynamical Transfemoral Prosthesis with EdgeDRNN Accelerator." In the proceedings of 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020.

EILE: Efficient Incremental Learning on the Edge

Published in In the proceedings of 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021

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Recommended citation: Xi Chen, Chang Gao, Tobi Delbruck, Shih-Chii Liu, "EILE: Efficient Incremental Learning on the Edge." In the proceedings of 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021.

A 23$mu$W Solar-Powered Keyword Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction

Published in In the proceedings of 2022 IEEE International Solid-State Circuits Conference (ISSCC), 2022

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Recommended citation: Kwantae Kim*, Chang Gao*, Rui Gra\c{c}a, Ilya Kiselev, Hoi-Jun Yoo, Tobi Delbruck, Shih-Chii Liu, "A 23$mu$W Solar-Powered Keyword Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction." In the proceedings of 2022 IEEE International Solid-State Circuits Conference (ISSCC), 2022.

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