Zobrazeno 1 - 10
of 624
pro vyhledávání: '"LI Erping"'
Autor:
Wei Maoliang, Lin Xiaobin, Xu Kai, Wu Yingchun, Wang Chi, Wang Zijia, Lei Kunhao, Bao Kangjian, Li Junying, Li Lan, Li Erping, Lin Hongtao
Publikováno v:
Nanophotonics, Vol 13, Iss 12, Pp 2183-2192 (2024)
In the development of silicon photonics, the continued downsizing of photonic integrated circuits will further increase the integration density, which augments the functionality of photonic chips. Compared with the traditional design method, inverse
Externí odkaz:
https://doaj.org/article/b4a79c5ea2294e51a9bb1256fb301eef
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 34, Iss 3, Pp 577-581 (2022)
ObjectiveTo understand the public’s ability to distinguish online food and drug rumors and false publicity， so as to prevent the spread of rumors and maintain social stability.MethodsA questionnaire survey， by the method of random sampling， w
Externí odkaz:
https://doaj.org/article/584950dd5c5144e0b9ee5f4b950799f9
Recent insights have revealed that rate-coding is a primary form of information representation captured by surrogate-gradient-based Backpropagation Through Time (BPTT) in training deep Spiking Neural Networks (SNNs). Motivated by these findings, we p
Externí odkaz:
http://arxiv.org/abs/2410.11488
Autor:
Lin, Xiaobin, Wei, Maoliang, Lei, Kunhao, Wang, Zijia, Wang, Chi, Ma, Hui, Ye, Yuting, Zhan, Qiwei, Li, Da, Dai, Shixun, Zhang, Baile, Hu, Xiaoyong, Li, Lan, Li, Erping, Lin, Hongtao
On-chip structured light, with potentially infinite complexity, has emerged as a linchpin in the realm of integrated photonics. However, the realization of arbitrarily tailoring a multitude of light field dimensions in complex media remains a challen
Externí odkaz:
http://arxiv.org/abs/2405.18666
Autor:
Xie, Xinrong, Liang, Gan, Ma, Fei, Du, Yulin, Peng, Yiwei, Li, Erping, Chen, Hongsheng, Li, Linhu, Gao, Fei, Xue, Haoran
Wave localization is a fundamental phenomenon that appears universally in both natural materials and artificial structures and plays a crucial role in understanding the various physical properties of a system. Usually, a localized state has an expone
Externí odkaz:
http://arxiv.org/abs/2402.04716
Traditional end-to-end (E2E) training of deep networks necessitates storing intermediate activations for back-propagation, resulting in a large memory footprint on GPUs and restricted model parallelization. As an alternative, greedy local learning pa
Externí odkaz:
http://arxiv.org/abs/2312.07636
Publikováno v:
Frontiers in neuroscience, 2022, 12
Spiking Neural Networks (SNNs), as one of the algorithmic models in neuromorphic computing, have gained a great deal of research attention owing to temporal information processing capability, low power consumption, and high biological plausibility. T
Externí odkaz:
http://arxiv.org/abs/2210.05241
Publikováno v:
Frontiers in neuroscience, 2022, 09
Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks
Externí odkaz:
http://arxiv.org/abs/2204.09893
Publikováno v:
Front. Phys. 10:906399 (2022)
The tensor network, as a facterization of tensors, aims at performing the operations that are common for normal tensors, such as addition, contraction and stacking. However, due to its non-unique network structure, only the tensor network contraction
Externí odkaz:
http://arxiv.org/abs/2203.16338
Metasurfaces have received a lot of attentions recently due to their versatile capability in manipulating electromagnetic wave. Advanced designs to satisfy multiple objectives with non-linear constraints have motivated researchers in using machine le
Externí odkaz:
http://arxiv.org/abs/2203.00002