Publications
Analog Circuits for Mixed-Signal Neuromorphic Computing Architectures in 28 nm FD-SOI Technology
Ning Qiao and Giacomo Indiveri, Automatic Gain Control of Ultra-Low Leakage Synaptic Scaling Homeostatic Plasticity Circuits, Biomedical Circuits and Systems (BIOCAS) 2016
Automatic Gain Control of Ultra-Low Leakage Synaptic Scaling Homeostatic Plasticity Circuits
Ning Qiao, Giacomo Indiveri, Chiara Bartolozzi, Automatic Gain Control of Ultra-Low Leakage Synaptic Scaling Homeostatic Plasticity Circuits, Biomedical Circuits and Systems (BIOCAS) 2016
An Auto-Scaling Wide Dynamic Range Current to Frequency Converter for Real-Time Monitoring of Signals in Neuromorphic Systems
Ning Qiao and Giacomo Indiveri, An Auto-Scaling Wide Dynamic Range Current to Frequency Converter for Real-Time Monitoring of Signals in Neuromorphic Systems Biomedical Circuits and Systems (BIOCAS) 2016
Scaling Mixed-Signal Neuromorphic Processors to 28 nm FD-SOI Technologies
Ning Qiao and Giacomo Indiveri, Automatic Gain Control of Ultra-Low Leakage Synaptic Scaling Homeostatic Plasticity Circuits , Biomedical Circuits and Systems (BIOCAS) 2016
An Ultralow Leakage Synaptic Scaling Homeostatic Plasticity Circuit With Configurable Time Scales up to 100 ks
Ning Qiao, Chiara Bartolozzi, Giacomo Indiver, An Ultralow Leakage Synaptic Scaling Homeostatic Plasticity Circuit With Configurable Time Scales up to 100 ks, IEEE Transactions on Biomedical Circuits and Systems, PP:(99), 2017
A differential memristive synapse circuit for on-line learning in neuromorphic computing systems
Nair, Manu V., Lorenz K. Muller, and Giacomo Indiveri. "A differential memristive synapse circuit for on-line learning in neuromorphic computing systems." Nano Futures 1.3 (2017): 035003.
Very large scale neuromorphic systems for biological signal processing
F.Catthoor, S.Mitra, A.Das, S.Schaafsma, Chapter in ``CMOS circuits for biological sensing and processing'' (eds. J.Cummings, S.Mitra), ISBN 978-3-319-67723-1, Springer, Heidelberg, Germany, Jan. 2018.
Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout
A.Das, P.Pradhapan, W.Groenendaal, P.Adiraju, R.T.Rajan, F.Catthoor, S.Schaafsma, J.L.Krichmar, N.Dutt, C.Van Hoof, CoRR, http://arxiv.org/abs/1708.05356, 2017. Accepted for Neural Networks, 2018.
Mapping of Local and Global Synapses on Spiking Neuromorphic Hardware
A.Das, Y.Wu, K.Huynh, F.Dell Anna, F.Catthoor and S.Schaafsma, accepted for Proc. 21th ACM/IEEE Design and Test in Europe Conf.(DATE), Dresden, Germany, March 2018.
Reconfigurable neuromorphic synapse interconnects with TFTs
J.Genoe, P.Raghavan, Z.Tokei, F.Catthoor, S.Steudel, Proc. 46th Europ. Solid-state Device Conf.(ESSDERC), Lausanne, Switzerland, pp.69-, Sep. 2016.
Reconfigurable neuromorphic synapse interconnects with TFT
S.Steudel, K.Myny, J.Stuijt, F.Catthoor, 1st Neuromorphic computing wsh., Grenoble, France, Nov. 2017. (only presentation)
An event-based classifier for dynamic vision sensor and synthetic data
Stromatias, E., Soto, M., Serrano Gotarredona, M. T., & Linares Barranco, B. (2017). An event-based classifier for Dynamic Vision Sensor and synthetic data. Frontiers in Neuroscience, 11(artículo 360).
Role of Al doping in the filament disruption in HfO2 resistance switches
S. Brivio, J. Frascaroli, and S. Spiga, Role of Al doping in the filament disruption in HfO2 resistance switches, Nanotechnology Vol. 28 Page 395202 (2017), DOI: 10.1088/1361-6528/aa8013.
Stochastic circuit breaker network model for bipolar resistance switching memories
S. Brivio and S. Spiga, Stochastic circuit breaker network model for bipolar resistance switching memories, Journal of Computation Electronics Vol. 16 Page 1154 (2017), DOI: 10.1007/s10825-017-1055-y
Resistive random access memory (RRAM) technology: From material, device, selector, 3D integration to bottom-up fabrication
H.-Yu Chen, S. Brivio, C.-C. Chang, J. Frascaroli, T.-H. Hou, B. Hudec, M. Liu, H. Lv, G. Molas, J. Sohn, S. Spiga, V. M. Teja, E. Vianello, H.-S. P.p Wong, Resistive random access memory (RRAM) technology: From material, device, selector, 3D integration to bottom-up fabrication, J Electroceramics, Volume 39, Issue 1–4, pp 21–38 (2017), DOI 10.1007/s10832-017-0095-9
Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing
J. Frascaroli, S. Brivio, E. Covi, and S. Spiga, Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing, Scientific Reports Vol. 8, 7178 (2018), DOI: 10.1038/s41598-018-25376-x
Spike-driven threshold-based learning with memristive synapses and neuromorphic silicon neurons
E. Covi, R. George, J. Frascaroli, S. Brivio, C. Mayr, H. Mostafa, G. Indiveri and S. Spiga, Spike-driven threshold-based learning with memristive synapses and neuromorphic silicon neurons, Journal of Physics D: Applied Physics Vol. 51 Page 344003 (2018), DOI: 10.1088/1361-6463/aad361
Hybrid Neural Network, An Efficient Low-Power Digital Hardware Implementation of Event-based Artificial Neural Network
Amirreza Yousefzadeh, Garrick Orchard, Evangelos Stromatias, Teresa Serrano-Gotarredona, and Bernabe Linares-Barranco, "Hybrid Neural Network, An Efficient Low-Power Digital Hardware Implementation of Event-based Artificial Neural Network," Circuits and Systems (ISCAS), 2018 IEEE International Symposium on, May 2018.
Performance Comparison of Time-Step-Driven versus Event-Driven Neural State Update Approaches in SpiNNaker
Amirreza Yousefzadeh, Mikel Soto, Teresa Serrano-Gotarredona, Francesco Galluppi, Luis Plana, Steve Furber, and Bernabe Linares-Barranco, "Performance Comparison of Time-Step-Driven versus Event-Driven Neural State Update Approaches in SpiNNaker," Circuits and Systems (ISCAS), 2018 IEEE International Symposium on, May 2018.
Event-Driven Configurable Module with Refractory Mechanism for ConvNets on FPGA
LA Camuñas-Mesa, Y Domínguez-Cordero, T Serrano-Gotarredona, and B Linares-Barranco, "Event-Driven Configurable Module with Refractory Mechanism for ConvNets on FPGA," Circuits and Systems (ISCAS), 2018 IEEE International Symposium on, May 2018.
Calibration of offset via bulk for low-power HfO2 based 1T1R memristive crossbar read-out system
C Mohan, LA Camuñas-Mesa, E Vianello, L Periniolla, C Reita, JM de la Rosa, T Serrano-Gotarredona, and B Linares-Barranco, "Calibration of offset via bulk for low-power HfO2 based 1T1R memristive crossbar read-out system," Microelectronic Engineering, vol. 198, pp. 35-47, Oct. 2018.
Very Large Scale Neuromorphic Systems For Biological Signal Processing
Francky Catthoor, Srinjoy Mitra, Anup Das and Siebren Schaafsma, "Very Large Scale Neuromorphic Systems For Biological Signal Processing", CMOS Circuits for Biological Sensing and Processing Systems, Springer, 2017
Power-Accuracy Trade-offs for Heartbeat Classification on Neural Networks Hardware
Adarsha Balaji, Federico Corradi, Anup Das, Sandeep Pande, Siebren Schaafsma, and Francky Catthoor, "Power-Accuracy Trade-offs for Heartbeat Classification on Neural Networks Hardware", Journal of Low Power Electronics (JOLPE), 2018
Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout
Anup Das, Paruthi Pradhapan, Willemijn Groenendaal, Prathyusha Adiraju, Raj Rajan, Francky Catthoor, Siebren Schaafsma, Jeff Krichmar, Nikil Dutt, and Chris Van Hoof, "Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout", Elsevier Neural Networks, 2018
Energy-Efficient Mapping of LTE-A PHY Signal Processing Tasks on Microservers
Anup Das, Francky Catthoor, Andre Bourdoux and Bert Gyselinckx, "Energy Efficient Mapping of LTE-A PHY Signal Processing Tasks on Microservers", IEEE Transactions on Green Communication and Networking, 2018
Heartbeat Classification in Wearables Using Multi-layer Perceptron and Time-Frequency Joint Distribution of ECG
Anup Das, Francky Catthoor, and Siebren Schaafsma, "Heartbeat Classification in Wearables Using Multi-layer Perceptron and Time-Frequency Joint Distribution of ECG", IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE-DL-EDGE-IOT), 2018
Mapping of Local and Global Synapses on Spiking Neuromorphic Hardware
Anup Das, Yuefeng Wu, Khanh Huynh, Francesco Dell Anna, Francky Catthoor and Siebren Schaafsma, "Mapping of Local and Global Synapses on Spiking Neuromorphic Hardware", Conference on Design, Automation and Test (DATE), 2018
Design-Technology Co-Optimization for OxRRAM-Based Synaptic Processing Unit
A. Mallik, D. Garbin, A. Fantini, D. Rodopoulos, R. Degraeve, J. Stuijt, Anup Das, S. Schaafsma, et al., "Design-Technology Co-Optimization for OxRRAM-Based Synaptic Processing Unit", Symposium on VLSI Technology (VLSIT), 2017
Computing optimal discrete readout weights in reservoir computing is NP-hard
F. Hadaeghi, H. Jaeger (2019): Computing optimal discrete readout weights in reservoir computing is NP-hard. Neurocomputing 338 (April 2019), 233-236
Reservoir Transfer on Analog Neuromorphic Hardware
X. He, T. Liu, F. Hadaeghi, H. Jaeger (2019): Reservoir Transfer on Analog Neuromorphic Hardware. Int. IEEE EMBS Conf. on Neural Engineering (NER '19) (3rd best paper award)
Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation
X. He and H. Jaeger (2018): Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation. International Conference on Learning Representations (ICLR 2018)
Overcoming Catastrophic Forgetting by Conceptors
X. He and H. Jaeger (2017): Overcoming Catastrophic Forgetting by Conceptors. Workshop on Dynamical Systems and Brain-Inspired Information Processing, Konstanz, October 2017 (best poster award)
Neuromorphic Electronic Systems for Reservoir Computing
F. Hadaeghi (2019, to appear): Neuromorphic Electronic Systems for Reservoir Computing. In: K. Nakajima, I. Fischer (eds): Reservoir Computing: Theory, Physical Implementations and Applications. Springer
