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Random-injection-based two-channel chaos with enhanced bandwidth and suppressed time-delay signature by mutually coupled lasers: Proposal and numerical analysis 被引量:2
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作者 Shi-Rong Xu Xin-Hong Jia +3 位作者 Hui-Liang Ma Jia-Bing Lin Wen-Yan Liang Yu-Lian Yang 《Chinese Physics B》 SCIE EI CAS CSCD 2021年第1期239-247,共9页
Simultaneous bandwidth(BW) enhancement and time-delay signature(TDS) suppression of chaotic lasing over a wide range of parameters by mutually coupled semiconductor lasers(MCSLs) with random optical injection are prop... Simultaneous bandwidth(BW) enhancement and time-delay signature(TDS) suppression of chaotic lasing over a wide range of parameters by mutually coupled semiconductor lasers(MCSLs) with random optical injection are proposed and numerically investigated. The influences of system parameters on TDS suppression(characterized by autocorrelation function(ACF) and permutation entropy(PE) around characteristic time) and chaos BW are investigated. The results show that, with the increasing bias current, the ranges of parameters(detuning and injection strength) for the larger BW(> 20 GHz) are broadened considerably, while the parameter range for optimized TDS(< 0.1) is not shrunk obviously.Under optimized parameters, the system can simultaneously achieve two chaos outputs with enhanced BW(> 20 GHz)and perfect TDS suppression. In addition, the system can generate two-channel high-speed truly physical random number sequences at 200 Gbits/s for each channel. 展开更多
关键词 random distributed feedback-based optical injection two-channel chaos lasing bandwidth enhancement and time-delay signature suppression physical random number generation
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Fast optical wavefront engineering for controlling light propagation in dynamic turbid media
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作者 Meiyun Xia Deyu Li +1 位作者 Ling Wang Daifa Wang 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2019年第4期46-66,共21页
While propagating inside the strongly scattering biological tssue,photons lose their incident directions beyond one transport mean free path(TMFP,~1 millimeter(mm)),which makes it challenging to achieve optical focusi... While propagating inside the strongly scattering biological tssue,photons lose their incident directions beyond one transport mean free path(TMFP,~1 millimeter(mm)),which makes it challenging to achieve optical focusing or clear imaging deep inside tissue.By manipulating many degrees of the incident optical wavefront,the latest optical wavefront engineering(WFE)technology compensates the wavelfront distortions caused by the scattering media and thus is toward breaking this physical limit,bringing bright perspective to many applications deep inside tissue,eg,high resolution functional/molecular imaging,optical excitation(optogenetics)and optical tweezers.However,inside the dynamic turbid media such as the biological tissue,the wavefront distortion is a fast and continuously changing process whose decorrelation rate is on timescales from milliseconds(ms)to microseconds(μs),or even faster.This requires that the WFE technology should be capable of beating this rapid process.In this review,we discuss the major challenges faced by the WFE technology due to the fast decorrelation of dynamic turbid media such as living tissue when achieving light focusing/imaging and summarize the research progress achieved to date to overcome these challenges. 展开更多
关键词 Fast wavefront engineering optical phase conjugation feedback-based iterative wavefront optimization transmission matrix decorrelation time
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Online distributed tracking of generalized Nash equilibrium on physical networks——Closing the Loop via Measurement Feedback 被引量:1
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作者 Yifan Su Feng Liu +2 位作者 Zhaojian Wang Shengwei Mei Qiang Lu 《Autonomous Intelligent Systems》 2021年第1期69-80,共12页
In generalized Nash equilibrium(GNE)seeking problems over physical networks such as power grids,the enforcement of network constraints and time-varying environment may bring high computational costs.Developing online ... In generalized Nash equilibrium(GNE)seeking problems over physical networks such as power grids,the enforcement of network constraints and time-varying environment may bring high computational costs.Developing online algorithms is recognized as a promising method to cope with this challenge,where the task of computing system states is replaced by directly using measured values from the physical network.In this paper,we propose an online distributed algorithm via measurement feedback to track the GNE in a time-varying networked resource sharing market.Regarding that some system states are not measurable and measurement noise always exists,a dynamic state estimator is incorporated based on a Kalman filter,rendering a closed-loop dynamics of measurement-feedback driven online algorithm.We prove that,with a fixed step size,this online algorithm converges to a neighborhood of the GNE in expectation.Numerical simulations validate the theoretical results. 展开更多
关键词 Generalized Nash equilibrium Distributed optimization Online optimization feedback-based optimization State estimation Sharing market
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