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Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling

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Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Electronics, Free Full-Text
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Frontiers in Neuroscience
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
PDF] Dendritic-Inspired Processing Enables Bio-Plausible STDP in Compound Binary Synapses
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Materials, Free Full-Text
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
PDF] Dendritic-Inspired Processing Enables Bio-Plausible STDP in Compound Binary Synapses
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
modeling and simulating - List of Frontiers' open access articles
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Frontiers in Neuroscience
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
PDF) Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Frontiers Engineering Spiking Neurons Using Threshold Switching Devices for High-Efficient Neuromorphic Computing
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Vishal Saxena's research works University of Delaware, Delaware (UDel UD) and other places
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
PDF] Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
PDF] ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
PDF] ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales
Frontiers Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling
Frontiers in Neuroscience
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