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Proposition of Adaptive Read Bias: A Solution to Overcome Power and Scaling Limitations in Ferroelectric‐Based Neuromorphic System [PDF]
Advanced ScienceHardware neuromorphic systems are crucial for the energy‐efficient processing of massive amounts of data. Among various candidates, hafnium oxide ferroelectric tunnel junctions (FTJs) are highly promising for artificial synaptic devices.
Ryun‐Han Koo +9 more
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Recent advances in neuromorphic transistors for artificial perception applications
Science and Technology of Advanced Materials, 2023 Conventional von Neumann architecture is insufficient in establishing artificial intelligence (AI) in terms of energy efficiency, computing in memory and dynamic learning.
Wei Sheng Wang, Li Qiang Zhu
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IEEE Access, 2023 This paper presents a new scalable $8\times8$ single photon avalanche diode (SPAD) based vision sensor with integrated spiking neuromorphic system on a single chip.
Mst Shamim Ara Shawkat +4 more
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Emerging memristive neurons for neuromorphic computing and sensing
Science and Technology of Advanced Materials, 2023 Inspired by the principles of the biological nervous system, neuromorphic engineering has brought a promising alternative approach to intelligence computing with high energy efficiency and low consumption.
Zhiyuan Li +4 more
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Advanced Intelligent Systems, 2021 Neuromorphic electronics draw attention as innovative approaches that facilitate hardware implementation of next‐generation artificial intelligent system including neuromorphic in‐memory computing, artificial sensory perception, and humanoid robotics ...
Sung Woon Cho +3 more
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A 3D-printed neuromorphic humanoid hand for grasping unknown objects
iScience, 2022 Summary: Compared with conventional von Neumann’s architecture-based processors, neuromorphic systems provide energy-saving in-memory computing. We present here a 3D neuromorphic humanoid hand designed for providing an artificial unconscious response ...
Chao Bao +3 more
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Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades [PDF]
, 2015 Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labelling existing ...
Ajinkya eJayawant +4 more
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Frontiers in Neuroscience, 2023 Increasing complexity and data-generation rates in cyber-physical systems and the industrial Internet of things are calling for a corresponding increase in AI capabilities at the resource-constrained edges of the Internet.
Mattias Nilsson +7 more
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Neuromorphic Learning towards Nano Second Precision [PDF]
, 2013 Temporal coding is one approach to representing information in spiking neural networks. An example of its application is the location of sounds by barn owls that requires especially precise temporal coding. Dependent upon the azimuthal angle, the arrival
Meier, Karlheinz +3 more
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SVITE: A Spike-Based VITE Neuro-Inspired Robot Controller [PDF]
, 2013 This paper presents an implementation of a neuro-inspired algorithm called VITE (Vector Integration To End Point) in FPGA in the spikes domain. VITE aims to generate a non-planned trajectory for reaching tasks in robots. The algorithm has been adapted
Domínguez Morales, Manuel Jesús +4 more
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