Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. Th...Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.展开更多
Neuromorphic devices that mimic the information processing function of biological synapses and neurons have attracted considerable attention due to their potential applications in brain-like perception and computing. ...Neuromorphic devices that mimic the information processing function of biological synapses and neurons have attracted considerable attention due to their potential applications in brain-like perception and computing. In this paper,neuromorphic transistors with W-doped In_(2)O_(3)nanofibers as the channel layers are fabricated and optoelectronic synergistic synaptic plasticity is also investigated. Such nanofiber transistors can be used to emulate some biological synaptic functions, including excitatory postsynaptic current(EPSC), long-term potentiation(LTP), and depression(LTD). Moreover, the synaptic plasticity of the nanofiber transistor can be synergistically modulated by light pulse and electrical pulse.At last, pulsed light learning and pulsed electrical forgetting behaviors were emulated in 5×5 nanofiber device array.Our results provide new insights into the development of nanofiber optoelectronic neuromorphic devices with synergistic synaptic plasticity.展开更多
The human brain that relies on neural networks communicated by spikes is featured with ultralow energy consumption, which is more robust and adaptive than any digital system. Inspired by the spiking framework of the b...The human brain that relies on neural networks communicated by spikes is featured with ultralow energy consumption, which is more robust and adaptive than any digital system. Inspired by the spiking framework of the brain, spike-based neuromorphic systems have recently inspired intensive attention. Therefore, neuromorphic devices with spike-based synaptic functions are considered as the first step toward this aim. Photoelectric neuromorphic devices are promising candidates for spike-based synaptic devices with low latency, broad bandwidth,and superior parallelism. Here, the indium-gallium-zinc-oxide-based photoelectric neuromorphic transistors are fabricated for Morse coding based on spike processing, 405-nm light spikes are used as synaptic inputs, and some essential synaptic plasticity, including excitatory postsynaptic current, short-term plasticity, and high-pass filtering, can be mimicked. More interestingly, Morse codes encoded by light spikes are decoded using our devices and translated into amplitudes. Furthermore, such devices are compatible with standard integrated processes suitable for large-scale integrated neuromorphic systems.展开更多
High-performance amorphous indium-gallium-zinc-oxide thin-film transistors(a-IGZO TFTs)gated by AlO/HfOstacked dielectric films are investigated.The optimized TFTs with AlO(2.0 nm)/HfO(13 nm)stacked gate dielectrics d...High-performance amorphous indium-gallium-zinc-oxide thin-film transistors(a-IGZO TFTs)gated by AlO/HfOstacked dielectric films are investigated.The optimized TFTs with AlO(2.0 nm)/HfO(13 nm)stacked gate dielectrics demonstrate the best performance,including low total trap density Nt,low subthreshold swing voltage,large switching ratio I/,high mobilityμ,and low operating voltage,equal to 1.35×10cm,88 mV/dec,5.24×10~8,14.2 cm~2/V·s,and 2.0 V,respectively.Furthermore,a low-voltage-operated resistor-loaded inverter has been fabricated based on such an a-IGZO TFT,showing ideal full swing characteristics and high gain of~27 at 3.0 V.These results indicate a-IGZO TFTs gated by optimized AlO/HfOstacked dielectrics are of great interests for low-power,high performance,and large-area display and emerging electronics.展开更多
基金Project supported by the National Key Research and Development Program of China (Grant Nos. 2021YFA1202600 and 2023YFE0208600)in part by the National Natural Science Foundation of China (Grant Nos. 62174082, 92364106, 61921005, 92364204, and 62074075)。
文摘Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.
基金Project supported by the National Key Research and Development Program of China (Grant Nos. 2021YFA1200051 and 2019YFB2205400)the National Natural Science Foundation of China (Grant Nos. 62174082 and 62074075)。
文摘Neuromorphic devices that mimic the information processing function of biological synapses and neurons have attracted considerable attention due to their potential applications in brain-like perception and computing. In this paper,neuromorphic transistors with W-doped In_(2)O_(3)nanofibers as the channel layers are fabricated and optoelectronic synergistic synaptic plasticity is also investigated. Such nanofiber transistors can be used to emulate some biological synaptic functions, including excitatory postsynaptic current(EPSC), long-term potentiation(LTP), and depression(LTD). Moreover, the synaptic plasticity of the nanofiber transistor can be synergistically modulated by light pulse and electrical pulse.At last, pulsed light learning and pulsed electrical forgetting behaviors were emulated in 5×5 nanofiber device array.Our results provide new insights into the development of nanofiber optoelectronic neuromorphic devices with synergistic synaptic plasticity.
基金supported by the National Key Research and Development Program of China (Grant No. 2019YFB2205400)the National Natural Science Foundation of China (Grant No. 62074075)
文摘The human brain that relies on neural networks communicated by spikes is featured with ultralow energy consumption, which is more robust and adaptive than any digital system. Inspired by the spiking framework of the brain, spike-based neuromorphic systems have recently inspired intensive attention. Therefore, neuromorphic devices with spike-based synaptic functions are considered as the first step toward this aim. Photoelectric neuromorphic devices are promising candidates for spike-based synaptic devices with low latency, broad bandwidth,and superior parallelism. Here, the indium-gallium-zinc-oxide-based photoelectric neuromorphic transistors are fabricated for Morse coding based on spike processing, 405-nm light spikes are used as synaptic inputs, and some essential synaptic plasticity, including excitatory postsynaptic current, short-term plasticity, and high-pass filtering, can be mimicked. More interestingly, Morse codes encoded by light spikes are decoded using our devices and translated into amplitudes. Furthermore, such devices are compatible with standard integrated processes suitable for large-scale integrated neuromorphic systems.
基金supported by the National Key Research and Development Program of China(Grant Nos.2019YFB2205400 and 2021YFA1200051)the National Natural Science Foundation of China(Grant No.62074075)。
文摘High-performance amorphous indium-gallium-zinc-oxide thin-film transistors(a-IGZO TFTs)gated by AlO/HfOstacked dielectric films are investigated.The optimized TFTs with AlO(2.0 nm)/HfO(13 nm)stacked gate dielectrics demonstrate the best performance,including low total trap density Nt,low subthreshold swing voltage,large switching ratio I/,high mobilityμ,and low operating voltage,equal to 1.35×10cm,88 mV/dec,5.24×10~8,14.2 cm~2/V·s,and 2.0 V,respectively.Furthermore,a low-voltage-operated resistor-loaded inverter has been fabricated based on such an a-IGZO TFT,showing ideal full swing characteristics and high gain of~27 at 3.0 V.These results indicate a-IGZO TFTs gated by optimized AlO/HfOstacked dielectrics are of great interests for low-power,high performance,and large-area display and emerging electronics.
