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Temporal waveform denoising using deep learning for injection laser systems of inertial confinement fusion high-power laser facilities
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作者 Wei Chen Xinghua Lu +1 位作者 Wei Fan Xiaochao Wang 《High Power Laser Science and Engineering》 CSCD 2024年第6期207-220,共14页
For the pulse shaping system of the SG-Ⅱ-up facility, we propose a U-shaped convolutional neural network that integrates multi-scale feature extraction capabilities, an attention mechanism and long short-term memory ... For the pulse shaping system of the SG-Ⅱ-up facility, we propose a U-shaped convolutional neural network that integrates multi-scale feature extraction capabilities, an attention mechanism and long short-term memory units, which effectively facilitates real-time denoising of diverse shaping pulses. We train the model using simulated datasets and evaluate it on both the simulated and experimental temporal waveforms. During the evaluation of simulated waveforms, we achieve high-precision denoising, resulting in great performance for temporal waveforms with frequency modulationto-amplitude modulation conversion(FM-to-AM) exceeding 50%, exceedingly high contrast of over 300:1 and multistep structures. The errors are less than 1% for both root mean square error and contrast, and there is a remarkable improvement in the signal-to-noise ratio by over 50%. During the evaluation of experimental waveforms, the model can obtain different denoised waveforms with contrast greater than 200:1. The stability of the model is verified using temporal waveforms with identical pulse widths and contrast, ensuring that while achieving smooth temporal profiles,the intricate details of the signals are preserved. The results demonstrate that the denoising model, trained utilizing the simulation dataset, is capable of efficiently processing complex temporal waveforms in real-time for experiments and mitigating the influence of electronic noise and FM-to-AM on the time–power curve. 展开更多
关键词 deep learning frequency modulation-to-amplitude modulation conversion inertial confinement fusion SG-II facility temporal waveform denoising
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Localized temporal variation of Earth's inner-core boundary from high-quality waveform doublets 被引量:1
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作者 Danhua Xin Xiaodong Song Tao Wang 《Earthquake Science》 CSCD 2015年第3期175-185,共11页
The topography of the inner core is crucial to understand its growth process and interaction with the geodynamo. With the accuracy of teleseismic waveform doublets in determining the travel-time shifts between PKPcd a... The topography of the inner core is crucial to understand its growth process and interaction with the geodynamo. With the accuracy of teleseismic waveform doublets in determining the travel-time shifts between PKPcd and PKPdf inner-core phases, we examined the temporal change of the inner-core boundary sampled by new earthquake doublets that occurred in the Western Pacific and those previously found from the South Sandwich Islands. The receiver stations are those within the distance range of 128°–142° from the hypocenters of the waveform doublets. Our results suggest that temporal changes in PKPcd-PKPdf differential times are very subtle except some isolated regions under central America and Africa. The observations may indicate localized topography of the inner core and/or the inner-core boundary as transient slurry in isolated regions. 展开更多
关键词 waveform doublet Inner-core boundary topography temporal change PKP
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