Literature DB >> 25680215

A Biological-Realtime Neuromorphic System in 28 nm CMOS Using Low-Leakage Switched Capacitor Circuits.

Christian Mayr, Johannes Partzsch, Marko Noack, Stefan Hänzsche, Stefan Scholze, Sebastian Höppner, Georg Ellguth, Rene Schüffny.   

Abstract

A switched-capacitor (SC) neuromorphic system for closed-loop neural coupling in 28 nm CMOS is presented, occupying 600 um by 600 um. It offers 128 input channels (i.e., presynaptic terminals), 8192 synapses and 64 output channels (i.e., neurons). Biologically realistic neuron and synapse dynamics are achieved via a faithful translation of the behavioural equations to SC circuits. As leakage currents significantly affect circuit behaviour at this technology node, dedicated compensation techniques are employed to achieve biological-realtime operation, with faithful reproduction of time constants of several 100 ms at room temperature. Power draw of the overall system is 1.9 mW.

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Year:  2015        PMID: 25680215     DOI: 10.1109/TBCAS.2014.2379294

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  6 in total

Review 1.  Plasticity in memristive devices for spiking neural networks.

Authors:  Sylvain Saïghi; Christian G Mayr; Teresa Serrano-Gotarredona; Heidemarie Schmidt; Gwendal Lecerf; Jean Tomas; Julie Grollier; Sören Boyn; Adrien F Vincent; Damien Querlioz; Selina La Barbera; Fabien Alibart; Dominique Vuillaume; Olivier Bichler; Christian Gamrat; Bernabé Linares-Barranco
Journal:  Front Neurosci       Date:  2015-03-02       Impact factor: 4.677

2.  Switched-capacitor realization of presynaptic short-term-plasticity and stop-learning synapses in 28 nm CMOS.

Authors:  Marko Noack; Johannes Partzsch; Christian G Mayr; Stefan Hänzsche; Stefan Scholze; Sebastian Höppner; Georg Ellguth; Rene Schüffny
Journal:  Front Neurosci       Date:  2015-02-02       Impact factor: 4.677

3.  Breaking Liebig's Law: An Advanced Multipurpose Neuromorphic Engine.

Authors:  Runchun Wang; André van Schaik
Journal:  Front Neurosci       Date:  2018-08-29       Impact factor: 4.677

4.  Hardware-Based Hopfield Neuromorphic Computing for Fall Detection.

Authors:  Zheqi Yu; Adnan Zahid; Shuja Ansari; Hasan Abbas; Amir M Abdulghani; Hadi Heidari; Muhammad A Imran; Qammer H Abbasi
Journal:  Sensors (Basel)       Date:  2020-12-17       Impact factor: 3.576

5.  Unsupervised learning of digit recognition using spike-timing-dependent plasticity.

Authors:  Peter U Diehl; Matthew Cook
Journal:  Front Comput Neurosci       Date:  2015-08-03       Impact factor: 2.380

Review 6.  Qualitative-Modeling-Based Silicon Neurons and Their Networks.

Authors:  Takashi Kohno; Munehisa Sekikawa; Jing Li; Takuya Nanami; Kazuyuki Aihara
Journal:  Front Neurosci       Date:  2016-06-15       Impact factor: 4.677

  6 in total

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