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Observing the collapse of super-Bloch oscillations in strong-driving photonic temporal lattices

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Advanced Photonics 2024年第4期6卷 14-24页

作者： Xinyuan Hu Shulin Wang Chengzhi Qin Chenyu Liu Lange Zhao Yinglan Li Han Ye Weiwei Liu Stefano Longhi Peixiang Lu Bing Wang Huazhong University of Science and Technology School of PhysicsWuhan National Laboratory for OptoelectronicsWuhanChina Wuhan institute of Technology Hubei Key Laboratory of Optical Information and Pattern RecognitionWuhanChina Politecnico di Milano Dipartimento di FisicaMilanoItaly IFISC(UIB-CSIC) Instituto de Fisica Interdisciplinary Sistemas ComplejosPalma de MallorcaSpain

Super-Bloch oscillations(SBOs)are amplified versions of direct current(dc)-driving Bloch oscillations realized under the detuned dc-and alternating current(ac)-driving electric fields.A unique feature of SBOs is the coherent oscillation inhibition via the ac-driving renormalization effect,which is dubbed as the collapse of ***,previous experimental studies on SBOs have only been limited to the weak ac-driving regime,and the collapse of SBOs has not been ***,by harnessing a synthetic temporal lattice in fiber-loop systems,we push the ac-field into a strong-driving regime and observe the collapse of SBOs,which manifests as the oscillation-trajectory localization at specific ac-driving amplitudes and oscillation-direction flip by crossing collapse *** adopting arbitrary-wave ac-driving fields,we also realize generalized SBOs with engineered collapse ***,we exploit the oscillation-direction flip features to design tunable temporal beam routers and *** initiate and demonstrate the collapse of SBOs,which may feature applications in coherent wave localization control for optical communications and signal processing.

关键词： super-Bloch oscillations band collapse ac-driving renormalization effect photonic temporal lattices strong-driving regime

FIFAWC: a dataset with detailed annotation and rich semantics for group activity recognition

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Frontiers of Computer Science 2024年第06期18卷 186351-186351页

作者： PEI Duoxuan HUANG Di WANG Yunhong State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Intelligent recognition and image processing Lab. School of Computer Science and Engineering Beihang University

In this letter, we propose the FIFAWC dataset for GAR, offering unique features compared to existing ones. FIFAWC is meticulously annotated with all included GAs per sample augmenting both practicality and challenge. ... 详细信息

关键词： Semantics

Speckle reduction of SAR images using ICA basis enhancement and separation

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Chinese Optics Letters 2007年第9期5卷 509-512页

作者：李昱彤周越 institute of image processing and pattern recognition Shanghai Jiao Tong University

An approach for synthetic aperture radar （SAR） image de-noising based on independent component analysis （ICA） basis images is proposed. Firstly, the basis images and the code matrix of the original image are obtained using ICA algorithm. Then, pointwise Hoder exponent of each basis is computed as a cost criterion for basis enhancement, and then the enhanced basis images are classified into two sets according to a separation rule which separates the clean basis from the original basis. After these key procedures for speckle reduction, the clean image is finally obtained by reconstruction on the clean basis and original code matrix. The reconstructed image shows better visual perception and image quality compared with those obtained by other traditional techniques.

关键词： Algorithms image quality Independent component analysis Speckle Synthetic aperture radar

Distributed cubature Kalman filter based on observation bootstrap sampling

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High Technology Letters 2016年第2期22卷 142-147页

作者：胡振涛 Hu Yumei Zheng Shanshan Li Xian Guo Zhen institute of image processing and pattern recognition Henan University

Aiming at the adverse effect caused by observation noise on system state estimation precision,a novel distributed cubature Kalman filter(CKF) based on observation bootstrap sampling is ***,combining with the extraction and utilization of the latest observation information and the prior statistical information from observation noise modeling,an observation bootstrap sampling strategy is *** objective is to deal with the adverse influence of observation uncertainty by increasing observations ***,the strategy is dynamically introduced into the cubature Kalman filter,and the distributed fusion framework of filtering realization is *** filtering precision is obtained by promoting observation reliability without increasing the hardware cost of observation *** analysis and simulation results show the proposed algorithm feasibility and effectiveness.

关键词： state estimation cubature Kalman filter (CKF) observation bootstrap sampling distributed weighted fusion

Two-stage prediction and update particle filtering algorithm based on particle weight optimization in multi-sensor observation

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High Technology Letters 2014年第1期20卷 34-41页

作者：胡振涛 Liu Xianxing Li Jie institute of image processing and pattern recognition Henan University

The reasonable measuring of particle weight and effective sampling of particle state are consid- ered as two important aspects to obtain better estimation precision in particle filter. Aiming at the comprehensive treatment of above problems, a novel two-stage prediction and update particle filte- ring algorithm based on particle weight optimization in multi-sensor observation is proposed. Firstly, combined with the construction of muhi-senor observation likelihood function and the weight fusion principle, a new particle weight optimization strategy in multi-sensor observation is presented, and the reliability and stability of particle weight are improved by decreasing weight variance. In addi- tion, according to the prediction and update mechanism of particle filter and unscented Kalman fil- ter, a new realization of particle filter with two-stage prediction and update is given. The filter gain containing the latest observation information is used to directly optimize state estimation in the frame- work, which avoids a large calculation amount and the lack of universality in proposal distribution optimization way. The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.

关键词： multi-sensor information fusion particle filter weight optimization predictionand update

A Research Mode Based Evolutionary Algorithm for Many-Objective Optimization

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Chinese Journal of Electronics 2019年第4期28卷 764-772页

作者： CHEN Guoyu LI Junhua Key Laboratory of Jiangxi Province for image processing and pattern recognition Nanchang Hangkong University

The development of algorithms to solve Many-objective optimization problems(MaOPs) has attracted significant research interest in recent *** various types of Pareto front(PF) is a daunting challenge for evolutionary algorithm. A Research mode based evolutionary algorithm(RMEA) is proposed for many-objective optimization. The archive in the RMEA is used to store non-dominated solutions that can reflect the shape of the PF to guide the reference vector *** concerning the population is collected, once the number of non-dominated solutions reaches its limit after many generations without exceeding a given threshold, RMEA introduces a research mode that generates more reference vectors to search through the solutions. The proposed algorithm showed competitive performance with four state-of-the-art evolutionary algorithms in a large number of experiments.

关键词： Many-objective optimization Reference vector Research mode Evolutionary algorithm

PHUI-GA: GPU-based efficiency evolutionary algorithm for mining high utility itemsets

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Journal of Systems Engineering and Electronics 2024年第4期35卷 965-975页

作者： JIANG Haipeng WU Guoqing SUN Mengdan LI Feng SUN Yunfei FANG Wei Jiangsu Provincial Engineering Laboratory of pattern recognition and Computational Intelligence Department of Computer Science and TechnologyJiangnan UniversityWuxi 214122China China Ship Scientific Research Center Wuxi 214082China Taihu Laboratory of Deepsea Technological Science Wuxi 214082China Department of Mathematics Nanjing UniversityNanjing 210023China

Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search *** have good running and mining performance,but they still require huge computational resource and may miss many *** to the good combination of EA and graphics processing unit(GPU),we propose a parallel genetic algorithm(GA)based on the platform of GPU for mining HUIM(PHUI-GA).The evolution steps with improvements are performed in central processing unit(CPU)and the CPU intensive steps are sent to GPU to eva-luate with multi-threaded *** show that the mining performance of PHUI-GA outperforms the existing *** mining 90%HUIs,the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.

关键词： high utility itemset mining(HUIM) graphics process-ing unit(GPU)parallel genetic algorithm(GA) mining perfor-mance

Bayesian moving object detection in dynamic scenes using an adaptive foreground model

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第12期10卷 1750-1758页

作者： Sheng-yang YU Fang-lin WANG Yun-feng XUE Jie YANG institute of image processing and pattern recognition Shanghai Jiao Tong University Shanghai 200240 China

Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation between neighboring pixels can be used to achieve high levels of detection accuracy in the presence of dynamic background. However, color similarity between foreground and background will cause many foreground pixels to be misclassified. In this paper, an adaptive foreground model is exploited to detect moving objects in dynamic scenes. The foreground model provides an effective description of foreground by adaptively combining the temporal persistence and spatial coherence of moving objects. Building on the advantages of MAP-MRF (the maximum a posteriori in the Markov random field) decision framework, the proposed method performs well in addressing the challenging problem of missed detection caused by similarity in color between foreground and background pixels. Experimental results on real dynamic scenes show that the proposed method is robust and efficient.

关键词： Moving object detection Foreground model Kernel density estimation (KDE) MAP-MRF estimation

New Method of Reconstruction from Nonparallel Stereo and Application to Surgical Navigator

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Journal of Shanghai Jiaotong university(Science) 2007年第6期12卷 707-712页

作者：王建华刘允才 inst. of image processing and pattern recognition Shanghai Jiaotong Univ.

A new method to reconstruct 3D scene points from nonparallel stereo is proposed. From a pair of conjugate images in an arbitrarily configured stereo system that has been calibrated, coordinates of 3D scene points can be computed directly using the method, bypassing the process of rectifying images or iterative solution involved in existing methods. Experiment results from both simulated data and real images validate the method. Practical application to surgical navigator shows that the method has advantages to improve efficiency and accuracy of 3D reconstruction from nonparallel stereo system in comparison with the conventional method that employs algorithm for standard parallel axes stereo geometry.

关键词： stereo nonparallel axes reconstruction method surgical navigator