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Marko Noack
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2020 – today
- 2020
- [j2]Johannes Partzsch
, Christian Mayr
Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System. J. Signal Process. Syst. 92(11): 1303-1321 (2020)
2010 – 2019
- 2019
- [i4]Johannes Partzsch, Christian Mayr, Massimiliano Giulioni, Marko Noack, Stefan Hänzsche, Stefan Scholze, Sebastian Höppner, Paolo Del Giudice, René Schüffny:
Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System. CoRR abs/1904.10389 (2019) - 2016
- [j1]Christian Mayr, Johannes Partzsch
A Biological-Realtime Neuromorphic System in 28 nm CMOS Using Low-Leakage Switched Capacitor Circuits. IEEE Trans. Biomed. Circuits Syst. 10(1): 243-254 (2016) - 2014
- [c4]Marko Noack, Markus Krause, Christian Mayr, Johannes Partzsch
VLSI implementation of a conductance-based multi-synapse using switched-capacitor circuits. ISCAS 2014: 850-853 - [i3]Christian Mayr, Michael Schultz, Marko Noack, Stephan Henker, Johannes Partzsch, René Schüffny:
OTA based 200 GΩ resistance on 700 μm2 in 180 nm CMOS for neuromorphic applications. CoRR abs/1409.0171 (2014) - [i2]Christian Mayr, Johannes Partzsch, Marko Noack, Stefan Hänzsche, Stefan Scholze, Sebastian Höppner, Georg Ellguth, René Schüffny:
A Biological-Realtime Neuromorphic System in 28 nm CMOS using Low-Leakage Switched Capacitor Circuits. CoRR abs/1412.3233 (2014) - [i1]Marko Noack, Johannes Partzsch, Christian Mayr, Stefan Hänzsche, Stefan Scholze, Sebastian Höppner, Georg Ellguth, René Schüffny:
Switched-Capacitor Realization of Presynaptic Short-Term-Plasticity and Stop-Learning Synapses in 28 nm CMOS. CoRR abs/1412.3243 (2014) - 2013
- [c3]Christian Mayr, Johannes Partzsch, Marko Noack, René Schüffny:
Live demonstration: Multiple-timescale plasticity in a neuromorphic system. ISCAS 2013: 666-670 - 2011
- [c2]Marko Noack, Christian Mayr, Johannes Partzsch
Synapse dynamics in CMOS derived from a model of neurotransmitter release. ECCTD 2011: 198-201 - 2010
- [c1]Christian Mayr, Marko Noack, Johannes Partzsch
Replicating experimental spike and rate based neural learning in CMOS. ISCAS 2010: 105-108
Coauthor Index
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