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arXiv 2024年

作者： Cong, Runmin Sheng, Ronghui Wu, Hao Guo, Yulan Wei, Yunchao Zuo, Wangmeng Zhao, Yao Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Shandong Jinan250061 China Artificial Intelligence Institute Beijing Normal University Beijing100875 China Changsha410073 China School of Electronics and Communication Engineering Sun Yat-sen University Guangzhou510275 China School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Lingnan University Hong Kong

Color information is the most commonly used prior knowledge for depth map super-resolution (DSR), which can provide high-frequency boundary guidance for detail restoration. However, its role and functionality in DSR have not been fully developed. In this paper, we rethink the utilization of color information and propose a hierarchical color guidance network to achieve DSR. On the one hand, the low-level detail embedding module is designed to supplement high-frequency color information of depth features in a residual mask manner at the low-level stages. On the other hand, the high-level abstract guidance module is proposed to maintain semantic consistency in the reconstruction process by using a semantic mask that encodes the global guidance information. The color information of these two dimensions plays a role in the front and back ends of the attention-based feature projection (AFP) module in a more comprehensive form. Simultaneously, the AFP module integrates the multi-scale content enhancement block and adaptive attention projection block to make full use of multi-scale information and adaptively project critical restoration information in an attention manner for DSR. Compared with the state-of-the-art methods on four benchmark datasets, our method achieves more competitive performance both qualitatively and quantitatively. The code and results can be found from the link of https://***/HCGNet_TIM2024. © 2024, CC BY-NC-SA.

关键词： Restoration

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Optimized Dispatching of Seawater Pumping-Storing/Wind/Solar Hybrid Power Generating system

Optimized Dispatching of Seawater Pumping-Storing/Wind/Solar...

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第40届中国控制会议

作者： Yuyu Liu Ding Liu Lu Kang National & Local Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Different power sources in Seawater Pumping-Storing/Wind/Solar Hybrid Power Generating system supply power to the island *** order to ensure the reliability of the power supplying and improve the economical efficiency of the island micro-grid system at the same time,the output of each power source in the island micro-grid system needs to be optimized and dispatched according to historical wind power and photo-voltaic *** this paper,the mathematical model of Seawater Pumping-Storing/Wind/Solar Hybrid Power Generating system is established,and the one-time cost,*** the joint system are taken as the objective *** immune particle swarm algorithm is used to figure out the optimal output of each power source in the system after considering the restrictions including power balance of the system,the power constraints of each generator set and the online power of wind power and *** example shows that the optimization result of improved PSO algorithm is better than the original one,and it can also achieve the optimized dispatching of the joint system economically and effectively.

关键词： Seawater pumped-storage power station IPSO Optimized Dispatching

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Real-time and ultrafast optical pulse quantization based on slicing the supercontinuum

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Chinese Optics Letters 2021年第8期19卷 69-74页

作者： Ya Guo Qiang Cai Zhiwei Jia Bingjie Xu Zhensen Gao Qianwu Zhang Ruonan Zhang Adonis Bogris K.Alan Shore Yuncai Wang Pu Li Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Communication Security Laboratory Institute of Southwestern CommunicationChengdu 610041China Department of Informatics and Computer Engineering University of West AtticaAthens 12243Greece School of Electronic Engineering Bangor UniversityWales LL571UTUnited Kingdom

All-optical analog-to-digital conversion is a paramount issue in modern science. How to implement real-time and ultrafast quantization to optical pulses with different intensities in an all-optical domain is a central problem. Here, we report a realtime demonstration of an all-optical quantization scheme based on slicing the supercontinuum in a nonlinear fiber. In comparison with previous schemes through off-line analysis of the power of different optical spectral components in the supercontinuum, this, to the best of our knowledge, is the first demonstration of such functionality online in the time ***, the extinction ratio among the quantized outputs can exceed 10 d B, which further confirms the feasibility of the proposed quantization scheme. The current 3 bit resolution in the proof-of-principle experiment is limited by the current experimental condition, but it can be expected to be greatly enhanced through improving both the spectral width of the generated supercontinuum and the number of filtering channels used.

关键词： all-optical analog-to-digital conversion photonic quantization all-optical signal processing supercontinuum generation

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A multi-agent jamming decision-making method based on SP-HASAC

A multi-agent jamming decision-making method based on SP-HAS...

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IET International Radar Conference (IRC 2023)

作者： Jingpeng Gao Chen Shen Lu Gao Zhiye Jiang College of Information and Communication Engineering Harbin Engineering University Harbin People's Republic of China Beijing Institute of Electronic System Engineering Beijing People's Republic of China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing People's Republic of China

ISBN: (数字)9781837240982

In the study of the multi-UAV penetration mission decision method, the Heterogeneous Agent Soft Actor-Critic algorithm uses the HAML framework and the maximum entropy principle to enable UAVs to have stronger anti-jamming capability and exploration capability. However, it is difficult to accurately evaluate the action value of UAVs and the training stability is poor. To address this issue, this paper proposes a multi-agent based on the state prediction-HASAC (SP-HASAC) jamming decision method. Based on the idea of advantage function decomposition and environmental dynamics model, the state prediction network is designed to extract more abundant spatial information of penetration battlefield and achieve accurate evaluation of the action value of multi-UAV. Combining with the negative domain activation theory, the ReLU function is improved to realize the stable training of multi-UAV. The simulation results show that in the electronic penetration scenario of three UAVs against a single radar, the training convergence time of the proposed improved algorithm is reduced by 22% compared with the original algorithm. Three UAVs penetration to twice the burn-through distance still has more than 70% penetration success rate.

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Downstream-agnostic Adversarial Examples

arXiv

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arXiv 2023年

作者： Zhou, Ziqi Hu, Shengshan Zhao, Ruizhi Wang, Qian Zhang, Leo Yu Hou, Junhui Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Wuhan University China School of Information and Communication Technology Griffith University Australia Department of Computer Science City University of Hong Kong Hong Kong National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab

Self-supervised learning usually uses a large amount of unlabeled data to pre-train an encoder which can be used as a general-purpose feature extractor, such that downstream users only need to perform fine-tuning operations to enjoy the benefit of "large model". Despite this promising prospect, the security of pre-trained encoder has not been thoroughly investigated yet, especially when the pre-trained encoder is publicly available for commercial use. In this paper, we propose AdvEncoder, the first framework for generating downstream-agnostic universal adversarial examples based on the pre-trained encoder. AdvEncoder aims to construct a universal adversarial perturbation or patch for a set of natural images that can fool all the downstream tasks inheriting the victim pre-trained encoder. Unlike traditional adversarial example works, the pre-trained encoder only outputs feature vectors rather than classification labels. Therefore, we first exploit the high frequency component information of the image to guide the generation of adversarial examples. Then we design a generative attack framework to construct adversarial perturbations/patches by learning the distribution of the attack surrogate dataset to improve their attack success rates and transferability. Our results show that an attacker can successfully attack downstream tasks without knowing either the pre-training dataset or the downstream dataset. We also tailor four defenses for pre-trained encoders, the results of which further prove the attack ability of AdvEncoder. Our codes are available at: https://github. com/CGCL-codes/AdvEncoder. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Hybrid integrated modeling of thermal field temperature in Cz silicon single crystal growth process based on VMD-CNN-LSTM-ELM

Hybrid integrated modeling of thermal field temperature in C...

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第40届中国控制会议

作者： Yin Wan Ding Liu Junchao Ren National & Local Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Czochralski（Cz） silicon single crystal growth is a dynamic time-varying process with complex physical changes,multi-phase coupling of multiple fields, model uncertainty and large hysteresis and nonlinearity, while mechanistic models based on a large number of assumptions are difficult to be applied practically. In order to establish a stable and reliable model of crystal growth process, this paper proposes a variational modal decomposition--convolutional neural network-long and short-term memory network-extreme learning machine（VMD-CNN-LSTM-ELM） nonlinear hybrid integrated modeling method based on the idea of data-driven modeling to construct a model between heater power and thermal field temperature. The model consists of feature extraction, deep learning network, and optimization algorithm. First, VMD is used to decompose the original data into multiple Intrinsic Mode Function（IMF） from low to high frequencies, preserving the variation characteristics of the signal at different frequencies. Second, for each eigenmode function sequence, CNN feature extraction and LSTM prediction are performed in turn. Then, ELM is used to nonlinearly integrate the prediction results of multiple sequences to obtain the final prediction output. Finally, the simulation experimental results based on industrial data show that the proposed VMD-LSTMELM based thermal field temperature has excellent prediction performance and generalization ability.

关键词： Cz silicon single crystal growth Data-driven modeling Thermal field temperature Hybrid integrated modeling

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Distributed MPC Algorithm for Linear Discrete systems with communication Noise

Distributed MPC Algorithm for Linear Discrete Systems with C...

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第40届中国控制会议

作者： Duqiao Zhao Ding Liu Linxiong Liu Xia Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xian University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

In this paper, a distributed MPC algorithm is proposed for linear discrete systems with bounded communication noise and random communication failure. Based on the characteristics of time-varying directed graphs, the convergence of the algorithm is analyzed in the case of communication noise and random communication failure. This algorithm uses the distributed projection dual subgradient algorithm to solve the dual problem and replaces the double stochastic condition of the traditional algorithm with row stochastic condition. The exponential stability of the system is guaranteed. Finally, an example is given to illustrate the performance of the algorithm.

关键词： Distributed MPC Bounded communication Noise Random communication Faults Distributed Projection Dual Subgradient Row Stochastic

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A Solution Scheme Based on Quantum Enhancement for Multi Classification Problems

SSRN

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SSRN 2022年

作者： Zhang, Yijun Mu, Xiaodong Zhang, Peng Zhao, Dao Institute of Information and Communication National University of Defense Technology Wuhan430079 China Graduate School Rocket Force University of Engineering Xi’an710025 China State Key Laboratory of Astronautics Dynamics Xi’an satellite control center Xi’an710043 China

With the increasing data size of multi classification problems, the running efficiency of classical algorithms is seriously affected. In the paper, we propose a solution scheme based on quantum enhancement binary tree support vector machine for multi classification problems. On the basis of Euclidean distance binary tree support vector machine, the scheme quantizes the sample data. Aiming at the two parts of Euclidean distance and kernel function which consume a lot of computing resources in the classical algorithm, a general quantum circuit for the inner product of quantum states is constructed. By combining the parallel computing ability of the quantum with the classical algorithm, the exponential acceleration of these two parts is realized. Aiming at the linear equation of the classical algorithm which consumes a lot of computing resources. A quantum circuit based on quantum singular value estimation is proposed. Using the acceleration advantage of the quantum computing in matrix computing, the quantum enhancement of this part is realized. The experimental results show the proposed scheme has at least polynomial reduction in the time complexity and spatial complexity compared with classical methods for solving multi classification problems. © 2022, The Authors. All rights reserved.

关键词： Support vector machines

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Non-Fourier Heat Conduction based on Self-Adaptive Weight Physics-Informed Neural Networks

Non-Fourier Heat Conduction based on Self-Adaptive Weight Ph...

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第40届中国控制会议

作者： Shuyan Shi Ding Liu Zhongdan Zhao National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shananxi Key Laboratory of Complex System Control and Intelligent Information Processing

This paper establishes the non-Fourier heat conduction model to describe the heat transfer process of mono-crystalline silicon under the condition of unstable thermal field and thermal shock in the Czochralski method.A novel differential equations solver called Physics-Informed Neural Networks（PINN） algorithm was *** with finite element method（FEM）,this method has some advantages like no grid requirement and easily *** order to deal with the unbalance of constraint condition and speed up the convergence,we propose a novel method called Self-Adaptive Weight Physics-Informed Neural Networks（SWPINN）.The comparison of the experimental results of SWPINN and COMSOL verifies the effectiveness of *** modifying the parameter of non-Fourier heat conduction model,this paper obtains the temperature distribution under different heat relaxation ***,comparison between SWPINN and PINN shows that the proposed method has faster convergence speed and higher accuracy.

关键词： Non-Fourier Heat Conduction Physics-Informed Neural Networks Partial Differential Equation Monocrystalline Silicon Czochralski Method

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Arbitrary State Transition of Open Qubit system Based on Switching control

arXiv

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arXiv 2024年

作者： Wu, Guangpu Xue, Shibei Ma, Shan Kuang, Sen Dong, Daoyi Petersen, Ian R. Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Automation Central South University Changsha410083 China Department of Automation University of Science and Technology of China Hefei230027 China School of Engineering Australian National University CanberraACT2601 Australia

We present a switching control strategy based on Lyapunov control for arbitrary state transitions in open qubit systems. With coherent vector representation, we propose a switching control strategy, which can prevent the state of the qubit from entering invariant sets and singular value sets, effectively driving the system ultimately to a sufficiently small neighborhood of target states. In comparison to existing works, this control strategy relaxes the strict constraints on system models imposed by special target states. Furthermore, we identify conditions under which the open qubit system achieves finite-time stability (FTS) and finite-time contractive stability (FTCS), respectively. This represents a critical improvement in quantum state transitions, especially considering the asymptotic stability of arbitrary target states is unattainable in open quantum systems. The effectiveness of our proposed method is convincingly demonstrated through its application in a qubit system affected by various types of decoherence, including amplitude, dephasing and polarization decoherence. Copyright © 2024, The Authors. All rights reserved.

关键词： Asymptotic stability

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