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Homogeneous neuromorphic hardware
Science, 2021Bifunctional ferroelectric transistors enable collocation of memory and ...
Feng, Rao, Xutang, Tao
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Neuromorphic nanoelectronic materials
Nature Nanotechnology, 2020Memristive and nanoionic devices have recently emerged as leading candidates for neuromorphic computing architectures. While top-down fabrication based on conventional bulk materials has enabled many early neuromorphic devices and circuits, bottom-up approaches based on low-dimensional nanomaterials have shown novel device functionality that often ...
Vinod K. Sangwan, Mark C. Hersam
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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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Scientific American, 2005
Compact, efficient electronics based on the brain's neural system could yield implantable silicon retinas to restore vision, as well as robotic eyes and other smart sensors.
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Compact, efficient electronics based on the brain's neural system could yield implantable silicon retinas to restore vision, as well as robotic eyes and other smart sensors.
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ACM SIGPLAN Notices, 2014
The desire to build a computer that operates in the same manner as our brains is as old as the computer itself. Although computer engineering has made great strides in hardware performance as a result of Dennard scaling, and even great advances in 'brain like' computation, the field still struggles to move beyond sequential, analytical computing ...
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The desire to build a computer that operates in the same manner as our brains is as old as the computer itself. Although computer engineering has made great strides in hardware performance as a result of Dennard scaling, and even great advances in 'brain like' computation, the field still struggles to move beyond sequential, analytical computing ...
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2021
The brain is not a glorified digital computer. It does not store information in registers, and it does not mathematically transform mental representations to establish perception or behavior. The brain cannot be downloaded to a computer to provide immortality, nor can it destroy the world by having its emerged consciousness traveling in cyberspace ...
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The brain is not a glorified digital computer. It does not store information in registers, and it does not mathematically transform mental representations to establish perception or behavior. The brain cannot be downloaded to a computer to provide immortality, nor can it destroy the world by having its emerged consciousness traveling in cyberspace ...
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Proceedings of the 48th International Symposium on Microarchitecture, 2015
A vast array of devices, ranging from industrial robots to self-driven cars or smartphones, require increasingly sophisticated processing of real-world input data (image, voice, radio, ...). Interestingly, hardware neural network accelerators are emerging again as attractive candidate architectures for such tasks.
Zidong Du +7 more
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A vast array of devices, ranging from industrial robots to self-driven cars or smartphones, require increasingly sophisticated processing of real-world input data (image, voice, radio, ...). Interestingly, hardware neural network accelerators are emerging again as attractive candidate architectures for such tasks.
Zidong Du +7 more
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Neuromorphic computing refers to neural-inspired systems designed for non–von Neumann architectures that integrate principles from neuroscience, machine learning, AI, hardware design, and materials science. Initially focused on analog circuits mimicking biological neurons and synapses, the field has expanded to encompass a broad range of hardware and ...
Tripti R, Kulkarni +2 more
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Tripti R, Kulkarni +2 more
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