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Research Units » Design and Test of Mixed-Signal Integrated Circuits » Neuromorphic Systems

Neuromorphic Systems

Contact:

Bernabé Linares Barranco

bernabeimse-cnmcsices

Teresa Serrano Gotarredona

tereseimse-cnmcsices

Keywords: spiking neural-circuits; signal-processing; learning; AER (address-event-representation); AER-contrast-retinas; AER-motion-retinas; AER-processors; AER-convolution; STDP (spike-timing-dependent-plasticity); low-power; frame-free-vision; convolutional-neural-networks

Description
The IMSE Neuromorphic group develops sensory and processing microchips that mimic sensing and processing in biological beings. It also develops multi-chip and hybrid chip-FPGA systems to scale up to higher complexity systems. The group also works on algorithms and sensory processing for spiking information sensing, coding and processing. Chips use mixed signal, low current, and/or low power, circuit techniques, as well as high speed communication techniques. The group uses mixed or digital CMOS technologies, as well as application projections exploiting emergent nanoscale technologies or new devices like memristors.
At present, the group focuses mainly on event-driven (spiking) frame-free vision systems, developing sensing retinas for spatial or temporal contrast (such as DVS -Dynamic Vision Sensors), as well as event-driven convolution processors, which allow to assemble for example large scale spiking 'Convolutional Neural Networks' for high speed object recognition. These chips and systems use AER (Address Event Representation) communication techniques.
Event-driven retinas do not produce sequences of still frames, as conventional video cameras do. Instead, each pixel senses light and computes a given property (spatial contrast, temporal change) continuously in time. Whenever this property exceeds a given threshold, the pixel sends out an event (which usually consists of the pixel x,y coordinate and the sign of the threshold), which is written onto one (or more) high speed bus with asynchronous handshaking. This way, sensors produce continuous event flows, and subsequent processors process them event by event.
Event-driven sensing-processing system with (a) DVS-retina and multi-kernel-convolver (b,c): it captures the 500Hz oscilloscope spiral (e), generating events (x,y,t), representing the spatio-temporal trajectory (d).
Event-driven shape sensing-recognition. (a) system, (b) stimulus, (c) events, (d-f) stages outputs showing 'clover' recognition simultaneous to stimulus.
Research Highlights
B. Linares-Barranco, "Memristors fire away", Nature Electronics, vol. 1, no. 2, pp. 100-101, 2018 » doi
L.A. Camuñas-Mesa, T. Serrano-Gotarredona, S. Ieng, R. Benosman and B. Linares-Barranco, "Event-driven Stereo Visual Tracking Algorithm to Solve Object Occlusion", IEEE Trans. on Neural Networks and Learning Systems, 2018 » doi
Yousefzadeh, M. Jablonski, T. Iakymchuk, A. Linares-Barranco, A. Rosado, L.A. Plana, S. Temple, T. Serrano-Gotarredona, S. Furber, and B. Linares-Barranco, "On Multiple AER Handshaking channels over High-Speed Bit-Serial Bi-Directional LVDS Links with Flow-Control and Clock-Correction on Commercial FPGAs for Scalable Neurmorphic Systems", IEEE Trans. on Biomedical Circuits and Systems, vol 11, no. 5, pp. 1133-1147, 2017 » doi
T. Serrano-Gotarredona and B. Linares-Barranco, "A 128x128 1.5% Contrast Sensitivity 0.9% FPN 3us Latency 4mW Asynchronous Frame-Free Dynamic Vision Sensor Using Transimpedance Amplifiers", IEEE J. Solid-State Circuits, IEEE Journal of Solid-State Circuits, vol. 48, no. 3, pp. 827-838, 2013 » doi
G. Indiveri, B. Linares-Barranco, R. Legenstein, G. Deligeorgis and T. Prodromakis, "Integration of nanoscale memristor synapses in neuromorphic computing architectures", Nanotechnology, vol. 24, no. 38, article number 384010, 2013 » doi
Key Research Projects & Contracts
NeuRAM3: Neural Computing Architectures in Advanced Monolithic 3D-VLSI Nano-Technologies » web
IP: Teresa Serrano-Gotarredona
Financia: Unión Europea, ICT (H2020)
Ene 2016 - Dic 2018
ECOMODE: Event-Driven Compressive Vision for Multimodal Interaction with Mobile Devices » web
IP: Bernabé Linares-Barranco
Financia: Unión Europea, ICT (H2020)
Ene 2015 - Dic 2018
HBP: Proyecto cerebro humano » web
IP: Bernabé Linares-Barranco
Financia: Unión Europea, FET-Flagship (H2020)
Abr 2014 - Mar 2016
CAVIAR: Convolution AER Vision Architecture
IP: Bernabé Linares-Barranco
Financia: Unión Europea, IST (VPM)
Jun 2002 - Jun 2006
NABAB: Nanocomputing building Blocks with acquired Behaviour
IP: Teresa Serrano Gotarredona
Financia: Unión Europea, ICT (FP7)
Abr 2007 - Abr 2010