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XNORBuilding
© 1980-2012 IEEE.A synaptic cell composed of two tunnel field-effect transistors (TFETs) which is capable of XNOR operation for binary neural networks has been experimentally demonstrated. Our proposed synaptic TFETs feature lower current during inference and higher programming efficiency during weight transfer than conventional synaptic transistors. Moreover, the fabricated synaptic TFET arrays satisfy the neurobiological energy requirement (~10 fJ per synaptic event) and low bit-error rate of 6.7×10-7%.N
Artificial neural networks (ANN) have demonstrated performance beyond human capability in challengin...
Abstract Photonic synaptic transistors are being investigated for their potential applications in ne...
As the basic and essential unit of neuromorphic computing systems, artificial synaptic devices have ...
Abstract — This paper studies the application of tunnel FET (TFET) in designing a low power and robu...
Neuromorphic computing, which mimics the structure and principles of the human brain, has the potent...
This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor trans...
The coming of the big-data era brought a need for power-efficient computing that cannot be realized ...
This dissertation explores cohesive design methodologies integrating emerging computing technologies...
A novel synaptic architecture based on a NAND flash memory structure is proposed as a high-density s...
We have developed a complementary pair of pFET and nFET floating-gate silicon MOS transistors for an...
In this work, a study on a semi-floating-gate synaptic transistor (SFGST) is performed to verify its...
The performance of computing systems has been increasingly choked by power consumption and memory ac...
We report on a 1-transisor/2-resistor (1T2R) synapse device with improved conductance linearity and ...
We report on an artificial synapse, an organic synapse-transistor (synapstor) working at 1 V and wit...
The explosive growth of data and information has motivated technological developments in computing s...
Artificial neural networks (ANN) have demonstrated performance beyond human capability in challengin...
Abstract Photonic synaptic transistors are being investigated for their potential applications in ne...
As the basic and essential unit of neuromorphic computing systems, artificial synaptic devices have ...
Abstract — This paper studies the application of tunnel FET (TFET) in designing a low power and robu...
Neuromorphic computing, which mimics the structure and principles of the human brain, has the potent...
This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor trans...
The coming of the big-data era brought a need for power-efficient computing that cannot be realized ...
This dissertation explores cohesive design methodologies integrating emerging computing technologies...
A novel synaptic architecture based on a NAND flash memory structure is proposed as a high-density s...
We have developed a complementary pair of pFET and nFET floating-gate silicon MOS transistors for an...
In this work, a study on a semi-floating-gate synaptic transistor (SFGST) is performed to verify its...
The performance of computing systems has been increasingly choked by power consumption and memory ac...
We report on a 1-transisor/2-resistor (1T2R) synapse device with improved conductance linearity and ...
We report on an artificial synapse, an organic synapse-transistor (synapstor) working at 1 V and wit...
The explosive growth of data and information has motivated technological developments in computing s...
Artificial neural networks (ANN) have demonstrated performance beyond human capability in challengin...
Abstract Photonic synaptic transistors are being investigated for their potential applications in ne...
As the basic and essential unit of neuromorphic computing systems, artificial synaptic devices have ...
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