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| 1 | A circular zone partition method for identifying Duffing oscillator state transition and its application to BPSK signal demodulation显示文摘When a Duffing oscillator is applied to signal detection, identifying its state transition is indispensable. Due to lack of an effective method for automatically distinguishing the state transition, phase analysis is extensively used. However, it needs ocular estimation to identify phase pattern corresponding to transition of Duffing oscillator. Hence it is not fit for communication signal demodulation. To solve the problem, this paper proposes a method, called circular zone partition (CZP), for partitioning trajectory on the phase plane of Duffing oscillator. First, a computing model for Duffing oscillator is described. Then, the fundamental principle and algorithm for the CZP method are discussed. Meanwhile the equation of a circular zone divider and its realization are presented. Thus, by way of the divider, the two-dimensional phase trajectory pattern of Duffing oscillator driven by an external signal can be transformed into the one-dimensional time signal, whose envelop after being filtered is able to indicate the state transition, i.e. the presence or the absence of external signal. Finally, to verify the effect of the CZP method on binary phase shifted keying (BPSK) signal demodulation, two examples are presented and simulation results show that this CZP method is accurate and valid for BPSK signal demodulation. | FU YongQing WU DongMei ZHANG Lin & LI XingYuan | 2011 | Science China(Information Sciences)2011，54，6： | 9 |
| 2 | Light gain amplification in microcavity organic semiconductor laser diodes under electrical pumping显示文摘Organic semiconductor is one of the most promising luminescent and lasing materials that can be chemically synthesized with a controllable performance and possess high cross-section of stimulated emission[1].Organic semiconductor laser diodes(OSLDs)can be prepared by simple processing technologies and integrated easily with other optoelectronic devices.As a result,OSLDs would | Jie Lin Yongsheng Hu Ying Lv Xiaoyang Guo Xingyuan Liu | 2017 | Science Bulletin2017，62，24： | 3 |
| 3 | All-optical computing based on convolutional neural networks显示文摘The rapid development of information technology has fueled an ever-increasing demand for ultrafast and ultralow-en-ergy-consumption computing.Existing computing instruments are pre-dominantly electronic processors,which use elec-trons as information carriers and possess von Neumann architecture featured by physical separation of storage and pro-cessing.The scaling of computing speed is limited not only by data transfer between memory and processing units,but also by RC delay associated with integrated circuits.Moreover,excessive heating due to Ohmic losses is becoming a severe bottleneck for both speed and power consumption scaling.Using photons as information carriers is a promising alternative.Owing to the weak third-order optical nonlinearity of conventional materials,building integrated photonic com-puting chips under traditional von Neumann architecture has been a challenge.Here,we report a new all-optical comput-ing framework to realize ultrafast and ultralow-energy-consumption all-optical computing based on convolutional neural networks.The device is constructed from cascaded silicon Y-shaped waveguides with side-coupled silicon waveguide segments which we termed“weight modulators”to enable complete phase and amplitude control in each waveguide branch.The generic device concept can be used for equation solving,multifunctional logic operations as well as many other mathematical operations.Multiple computing functions including transcendental equation solvers,multifarious logic gate operators,and half-adders were experimentally demonstrated to validate the all-optical computing performances.The time-of-flight of light through the network structure corresponds to an ultrafast computing time of the order of several picoseconds with an ultralow energy consumption of dozens of femtojoules per bit.Our approach can be further expan-ded to fulfill other complex computing tasks based on non-von Neumann architectures and thus paves a new way for on-chip all-optical computing. | Kun Liao Ye Chen Zhongcheng Yu Xiaoyong Hu Xingyuan Wang Cuicui Lu Hongtao Lin Qingyang Du Juejun Hu Qihuang Gong | 2021 | Opto-Electronic Advances2021，4，11： | 3 |
| 4 | Observer-based decen- tralized fuzzy neural sliding mode control for inter- connected unknown chaotic systems via network structure adaptation显示文摘 | Da Lin Wang Xingyuan | 2010 | Fuzzy Sets and Systems2010，161，15： | 1 |
| 5 | A bit-level image encryption algorithm based on spatiotemporal chaotic system and self-adaptive显示文摘 | Teng Lin Wang Xingyuan | 2012 | Optics Communications2012，285，8： | 1 |
| 6 | A novel colour image encryption algorithm based on chaos显示文摘 | Xingyuan Wang Lin Teng Xue Qin | 2011 | Signal Processing2011，，4： | 1 |
| 7 | Self-organizing adaptive fuzzy neural control for the synchronization of uncertain chaotic systems with random-varying parameters 显示文摘 | LIN Da WANG Xingyuan | 2011 | Neurocomputing2011，74，1213： | 1 |
| 8 | Association Between Lipid Profiles and Left Ventricular Hypertrophy:New Evidence from a Retrospective Study显示文摘Objective To explore the association between lipid profiles and left ventricular hypertrophy in a Chinese general population.Methods We conducted a retrospective observational study to investigate the relationship between lipid markers[including triglycerides,total cholesterol,low-density lipoprotein cholesterol,high-density lipoprotein(HDL)cholesterol,non-HDL-cholesterol,apolipoprotein A-I,apolipoprotein B,lipoprotein[a],and composite lipid profiles]and left ventricular hypertrophy.A total of 309,400 participants of two populations(one from Beijing and another from nationwide)who underwent physical examinations at different health management centers between 2009 and 2018 in China were included in the cross-sectional study.7,475 participants who had multiple physical examinations and initially did not have left ventricular hypertrophy constituted a longitudinal cohort to analyze the association between lipid markers and the new-onset of left ventricular hypertrophy.Left ventricular hypertrophy was measured by echocardiography and defined as an end-diastolic thickness of the mterventricular septum or left ventricle posterior wall>11 mm.The Logistic regression model was used in the cross-sectional study.Cox model and Cox model with restricted cubic splines were used in the longitudinal cohort.Results In the cross-sectional study for participants in the highest tertile of each lipid marker compared to the respective lowest,triglycerides[odds ratio(OR):1.2S0,95%CI:1.060 to 1.474],HDL-cholesterol(OR:0.780,95%CI:0.662 to 0.918),and lipoprotein(a)(OR:1.311,95%C7:1.115 to 1.541)had an association with left ventricular hypertrophy.In the longitudinal cohort,for participants in the highest tertile of each lipid marker at the baseline compared to the respective lowest,triglycerides[hazard ratio(HR):3.277,95%C/:1.720 to 6.244],HDL-cholesterol(HR:0.516,95%C7:0.283 to 0.940),non-HDL-cholesterol(HR:2.309,95%C/:1.296 to 4.112),apolipoprotein B(HR:2.244,95%CI:1.251 to 4.032)showed an association with new-onset left ventricular hypertrophy.In the Cox model with forward stepwise selection,triglycerides were the only lipid markers entered into the final model.Conclusion Lipids levels,especially triglycerides,are associated with left ventricular hypertrophy.Controlling triglycerides level potentiate to be a strategy in harnessing cardiac remodeling but deserve to be furdier investigated. | Xuewei Huang Keqiong Deng Juanjuan Qin Fang Lei Xingyuan Zhang Wenxin Wang Lijin Lin Yuming Zheng Dongai Yao Huiming Lu Feng Liu Lidong Chen Guilan Zhang Yueping Liu Qiongyu Yang Jingjing Cai Zhigang She Hongliang Li | 2022 | Chinese Medical Sciences Journal2022，37，2： | 1 |
| 9 | Dynamic fuzzy neural networks modeling and adaptive hackstepping tracking control of uncertain chaotic systems显示文摘 | LIN Da WANG Xingyuan NIAN Fuzhong | 2010 | Neurocomputing2010，73，： | 1 |
| 10 | Observer-based decentralized fuzzy neural sliding mode control for interconnected unknown chaotic systems via network structure adaptation显示文摘 | Da Lin Xingyuan Wang | 2010 | Fuzzy Sets and Systems2010，，15： | 1 |
| 11 | Dynamic fuzzy neural networks modeling and adaptive backstepping tracking control of uncertain chaotic systems显示文摘 | LIN Da WANG Xingyuan NIAN Fuzhong | | 0，，： | 1 |
| 12 | Observer-based decentralizedfuzzy neural sliding mode control for interconnected un-known chaotic systems via network structure adaptation显示文摘 | Lin Da Wang Xingyuan | 2010 | Fuzzy Sets and Systems2010，161，15： | 1 |
| 13 | Chaotic behavior in fractional-order memristor-based simplest chaotic circuit using fourth degree polynomial显示文摘 | Lin Teng Herbert H. C. Iu Xingyuan Wang Xiukun Wang | 2014 | Nonlinear Dynamics . 2014 (1-2)2014，，： | 1 |
| 14 | An image blocks encryptionalgorithm based on spatiotemporal chaos 显示文摘 | Wang Xingyuan Lin Teng | 2011 | NonlinearDynamics2011，67，1： | 1 |
| 15 | Chaotic behavior in fractional-order memristor-based simplest chaotic circuit using fourth degree polynomial显示文摘 | Lin Teng Herbert H. C. Iu Xingyuan Wang Xiukun Wang | 2014 | Nonlinear Dynamics2014，，1： | 1 |
| 16 | Dynamic fuzzy neural networks modeling and adaptive backstepping tracking control of uncertain chaotic systems显示文摘 | LIN DA WANG XINGYUAN NIAN FUZHONG et al | 2010 | Neuro-computing2010，73，： | 1 |
| 17 | A novel colour image encryption algorithm based on chaos显示文摘 | Xingyuan Wang Lin Teng Xue Qin | 2011 | Signal Processing2011，，4： | 1 |
| 18 | Synchronization of boolean networks with different update schemes显示文摘 | Zhang Hao Wang Xingyuan Lin Xiaohui | 2014 | IEEE/ACM Transactions on Computational Biology and Bioinformatics2014，11，5： | 1 |
| 19 | Stability and synchronization for discrete-time complex-valued neural networks with time-varying delays显示文摘 | Zhang Hao Wang Xingyuan Lin Xiaohui | 2014 | Plos One2014，9，4： | 1 |
| 20 | Investigating the dynamic memory effect of human drivers via ON-LSTM显示文摘It is a widely accepted view that considering the memory effects of historical information(driving operations)is beneficial for vehicle trajectory prediction models to improve prediction accuracy.However,many commonly used models(e.g.,long short-term memory,LSTM)can only implicitly simulate memory effects,but lack effective mechanisms to capture memory effects from sequence data and estimate their effective time range(ETR).This shortage makes it hard to dynamically configure the most suitable length of used historical information according to the current driving behavior,which harms the good understanding of vehicle motion.To address this problem,we propose a modified trajectory prediction model based on ordered neuron LSTM(ON-LSTM).We demonstrate the feasibility of ETR estimation based on ON-LSTM and propose an ETR estimation method.We estimate the ETR of driving fluctuations and lane change operations on the NGSIM I-80 dataset.The experiment results prove that the proposed method can well capture the memory effects during trajectory prediction.Moreover,the estimated ETR values are in agreement with our intuitions. | Shengzhe DAI Zhiheng LI Li LI Dongpu CAO Xingyuan DAI Yilun LIN | 2020 | Science China(Information Sciences)2020，63，9： | 1 |
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