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The operating system of the neuromorphic BrainScaleS-1 system
Neurocomputing, 2022 BrainScaleS-1 is a wafer-scale mixed-signal accelerated neuromorphic system targeted for research in the fields of computational neuroscience and beyond-von-Neumann computing. The BrainScaleS Operating System (BrainScaleS OS) is a software stack giving users the possibility to emulate networks described in the high-level network description language ...
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Current Opinion in Neurobiology, 2010
Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience.
Liu, S C, Delbruck, T
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Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience.
Liu, S C, Delbruck, T
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Benchmarking of Neuromorphic Hardware Systems
Proceedings of the Neuro-inspired Computational Elements Workshop, 2020With more and more neuromorphic hardware systems for the acceleration of spiking neural networks available in science and industry, there is a demand for platform comparison and performance estimation of such systems. This work describes selected benchmarks implemented in a framework with exactly this target: independent black-box benchmarking and ...
Christoph Ostrau +3 more
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2007
The essential functions of neurons can be emulated electronically on silicon chips. We describe such a neuron analogue, or neuromorph, that is compact and low power, with sufficient flexibility that it could perform as a general-purpose unit in networks for controlling robots or for use as implantable neural prostheses.
David P. M. Northmore +2 more
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The essential functions of neurons can be emulated electronically on silicon chips. We describe such a neuron analogue, or neuromorph, that is compact and low power, with sufficient flexibility that it could perform as a general-purpose unit in networks for controlling robots or for use as implantable neural prostheses.
David P. M. Northmore +2 more
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Neuromorphic Selective Attention Systems
Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03., 2003Selective attention mechanisms allow sensory systems with limited processing capacity to function in real time independent of the size of the stimulus input space. They can be particularly useful in vision systems, where the amount of information provided by the sensors typically exceeds the system's processing capacity.
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Reconfigurable neuromorphic computation in biochemical systems
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015Implementing application-specific computation and control tasks within a biochemical system has been an important pursuit in synthetic biology. Most synthetic designs to date have focused on realizing systems of fixed functions using specifically engineered components, thus lacking flexibility to adapt to uncertain and dynamically-changing environments.
Chiang, Hui-Ju +2 more
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Introduction to memristors and neuromorphic systems
Materials HorizonsXiaodong Chen, Cheol Seong Hwang, Yoeri van de Burgt and Francesca Santoro present a themed collection in Materials Horizons and Nanoscale Horizons gathering the latest developments in memristive materials, device fabrication, characterization and ...
Chen, Xiaodong +3 more
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Analog VLSI neuromorphic systems
1993 IEEE International Symposium on Circuits and Systems, 2002The implementation of neuromorphic systems in analog VLSI technology is discussed. As an example, a silicon retina (nearest neighborhood connectivity) and the H-J independent component analyzer (fully connected) auto-adaptive network with on-chip analog storage and learning circuitry are considered. >
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FeFETs for Neuromorphic Systems
2020Neuromorphic engineering represents one of the most promising computing paradigms for overcoming the limitations of the present-day computers in terms of energy efficiency and processing speed. While traditional neuromorphic circuits are based on complementary metal oxide semiconductor (CMOS) transistors and large capacitors, the recently emerging ...
Halid Mulaosmanovic +2 more
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