Article
Engineering, Electrical & Electronic
Yue Jiang, Wenjia Zhang, Fan Yang, Zuyuan He
Summary: This paper introduces a novel integrated photonic CNN based on double correlation operations and time-wavelength modulation. Testing on the MNIST dataset shows an accuracy of 85.5% for the photonic CNN, slightly lower than 86.5% achieved by a 64-bit computer. The study also analyzes the computing error of the photonic CNN and proposes a parallel photonic CNN based on a tensor processing unit.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Yang Sun, Jiayang Wu, Yang Li, Mengxi Tan, Xingyuan Xu, Sai Tak Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, David J. Moss
Summary: Photonic RF transversal signal processors, implemented with photonic technologies, offer high-speed information processing with reduced size, power consumption, and complexity. Optical microcombs generated from compact micro-resonators are ideal sources for RF photonics. This study provides a detailed analysis of the processing accuracy of microcomb-based photonic RF transversal signal processors. Theoretical limitations, practical error sources, and the relative contributions of both are investigated, highlighting the potential for further error reduction through feedback control.
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
(2023)
Article
Optics
Mengxi Tan, Xingyuan Xu, Jiayang Wu, Bill Corcoran, Andreas Boes, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, David J. Moss
Summary: Soliton crystal micro-combs are powerful tools for RF signal processing with multiple wavelength channels, offering compact size, multiple wavelengths, high versatility, and wide Nyquist bandwidths. This study demonstrates RF signal processing functions using a soliton crystal micro-comb and compares the results and trade-offs of different comb spacings, tap designs, and shaping methods.
Article
Computer Science, Information Systems
Zhongsen Sun, Kaizhuang Li, Yu Zheng, Xi Li, Yunlong Mao
Summary: Given the diversity of radar signals, this paper proposes an improved EfficientNetv2-s classification method based on deep learning for more precise classification and recognition of radar radiation source signals. The method uses 16 different types of radar signal parameters to generate random data sets consisting of spectrum images with varying amplitude. It replaces two-dimensional convolution in EfficientNetV2 with one-dimensional convolution and optimizes the channel attention mechanism to achieve better accuracy. Compared to other methods, this method has higher classification accuracy on the test set and lower complexity.
Article
Materials Science, Multidisciplinary
Yi Zhou, Junjie Zhan, Yifan Shao, Yubo Wang, Yongdi Dang, Sen Zhang, Hugo E. E. Hernandez-Figueroa, Yungui Ma
Summary: This study demonstrates a reconfigurable spatiotemporal optical signal processor using the phase-change material vanadium dioxide (VO2) to expand the processing bandwidth and enrich the operation functions. By controlling the operation temperature, a meta-device is designed that can switch between a first-order differentiator and a reflector in the spatiotemporal domain. The approach enables high-accuracy spatial and temporal signal processing, and holds great potential in applications such as remote sensing and fast imaging processing.
ADVANCED OPTICAL MATERIALS
(2023)
Article
Chemistry, Analytical
Yang Sun, Jiayang Wu, Yang Li, David J. Moss
Summary: RF photonic transversal signal processors combine reconfigurable electrical digital signal processing and high-bandwidth photonic processing for adaptive high-speed information processing. This paper compares the performance of processors implemented with discrete and integrated components, analyzes factors contributing to performance differences, and provides insights for future development.
Article
Optics
Yang Li, Yang Sun, Jiayang Wu, Guanghui Ren, Bill Corcoran, Xingyuan Xu, Sai T. Chu, Brent. E. Little, Roberto Morandotti, Arnan Mitchell, David J. Moss
Summary: In this study, we experimentally demonstrate the capability of microcomb-based MWP signal processors to handle diverse input signal waveforms, and quantify the processing accuracy for different waveforms. Theoretical analysis reveals the factors contributing to the difference in processing accuracy among different input waveforms.
Article
Optics
Xiangping Chen, Yang Jiang, Qiang Yu, Jing Xu, Yuejiao Zi, Jiahui Li, Xiaohong Lan, Na Chen
Summary: An all-photonic approach for generating and transforming microwave waveforms is proposed and experimentally demonstrated. Differentiators and a multiplier are used to transform an initial triangular waveform into square waveform and sawtooth (or reversed-sawtooth) waveform. Parabolic pulses are achieved and further transformed into sawtooth (or reversed-sawtooth) waveform. The feasibility of the system is verified through theoretical analysis and simulation, and the experimental results agree well with the theoretical analysis. This scheme provides a novel access to implement all-optical microwave waveforms generation, transformation, signal processing, and computing.
Article
Engineering, Electrical & Electronic
Simei Mao, Lirong Cheng, Fasial Nadeem Khan, Zihan Geng, Qian Li, H. Y. Fu
Summary: Optical computation, particularly optical neural networks, have received attention due to their high throughput and low energy consumption. A compact and general optical processor was demonstrated on a silicon-on-isolator platform, and a two-step trained tandem model based on deep convolutional neural networks was proposed to accelerate the design process of optical processors.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Kaveh Rahbardar Mojaver, Odile Liboiron-Ladouceur
Summary: We have designed a silicon photonics-based optical processor that utilizes multi-transverse modes to measure optical phase without conventional optical phase detection techniques. The processor exploits the different velocities of two quasi-transverse electric modes to convert optical phase to optical power. This design represents the first attempt to achieve a fully integrated programmable optical processor using multimode silicon photonics.
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Yamei Zhang, Ce Liu, Yu Zhang, Kunlin Shao, Cong Ma, Lu Li, Lijun Sun, Simin Li, Shilong Pan
Summary: A photonic-assisted multi-functional radar waveform generator has been proposed and experimentally demonstrated for single-chirped, counter-chirped, and dual-band linear frequency-modulated (LFM) microwave waveforms generation. By adjusting the time length and bandwidth of the rectangular LFM pulse, it is possible to generate single-chirped, counter-chirped or dual-band LFM signals.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2021)
Article
Optics
Bo Li, Ruihuan Wu, Weiyi Hong, Hongzhan Liu
Summary: This study proposes and demonstrates a correlation optical time domain reflectometry (COTDR) based on a broadband random optoelectronic oscillator (OEO). Unlike traditional COTDR that uses an external feedback semiconductor laser as the chaotic source, this scheme employs a random OEO as the random signal source. The generated signals have random and broadband characteristics, with frequencies not restricted by a fixed cavity length in the OEO, due to the randomly distributed feedback caused by the random fiber Bragg grating in the OEO. The experimental results show that the proposed COTDR achieves a range-independent spatial resolution of approximately 10 mm and a dynamic range of at least 78.47 km.
OPTICS AND LASER TECHNOLOGY
(2023)
Article
Engineering, Environmental
Huafu Pei, Fanhua Meng, Honghu Zhu
Summary: The study utilizes singular spectrum analysis and k-means algorithm for landslide displacement prediction, incorporating a one-dimensional convolutional neural network and a grey power model to consider time-varying inputs, improving prediction accuracy. Results show that the model can reasonably obtain periods representing different landslide states and accurately predict trend displacements.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Energy & Fuels
Shuangrui Jia, Yunfei Jia, Zewei Bu, Simeng Li, Liang Lv, Shengchang Ji
Summary: The detection of partial discharge (PD) in transformers is important for preventing insulation defects from becoming insulation failures. Optical detection method has strong anti-electromagnetic interference ability and unique advantages. In this study, an optical signal measuring device was designed to detect partial discharge inside the transformer and the characteristics of the optical signal were obtained.
Article
Chemistry, Multidisciplinary
Lorenzo De Marinis, Marco Cococcioni, Odile Liboiron-Ladouceur, Giampiero Contestabile, Piero Castoldi, Nicola Andriolli
Summary: This paper characterizes and compares two thermally tuned photonic integrated processors, based on silicon-on-insulator and silicon nitride platforms, for feature map extraction in convolutional neural networks. The reduction in bit resolution when crossing the processor is mainly due to optical losses, with the silicon-on-insulator chip ranging from 2.3-3.3 and the silicon nitride chip ranging from 1.3-2.4. However, the lower extinction ratio of Mach-Zehnder elements in the latter platform limits their expressivity to 75% compared to the former. Ultimately, the silicon-on-insulator processor outperforms the silicon nitride one in terms of footprint and energy efficiency.
APPLIED SCIENCES-BASEL
(2021)
