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Tsinghua Science and technology 2024年第2期29卷 368-385页

作者： Canyun Dai Xiaoyan Sun Hejuan Hu Yong Zhang Dunwei Gong School of information and control Engineering China University of Mining and TechnologyXuzhou 221116China School of information Science and technology Qingdao University of Science and TechnologyQingdao 266061China

The dispatch of integrated energy systems in coal mines(IES-CM)with mine-associated supplies is vital for efficient energy utilization and carbon emissions ***,IES-CM dispatch is highly challenging due to its feature as multi-objective and strong *** constrained multi-objective evolutionary algorithms often fall into locally feasible domains with poorly distributed Pareto front,which greatly deteriorates dispatch *** tackle this problem,we transform the traditional dispatch model of IES-CM into two tasks:the main task with all constraints and the helper task with constraint *** we propose a constraint adaptive multi-tasking differential evolution algorithm(CA-MTDE)to optimize these two tasks *** helper task with constraint adaptive is developed to obtain infeasible solutions near the feasible *** purpose of this infeasible solution is to transfer guiding knowledge to help the main task move away from local ***,a dynamic dual-learning strategy using DE/current-to-rand/1 and DE/current-to-best/1 is developed to maintain task diversity and ***,we comprehensively evaluate the performance of CA-MTDE by applying it to a coal mine in Shanxi Province,considering two IES-CM *** demonstrate the feasibility of CA-MTDE and its ability to generate a Pareto front with exceptional convergence,diversity,and distribution.

关键词： dispatch integrated energy system coal mine evolutionary multi-tasking constraint differential evolution

Generic and flexible self-correction method for nonlinearity-induced phase error in three-dimensional imaging

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Chinese Optics Letters 2024年第6期22卷 129-135页

作者： Jianhua Wang Peng Xu Yanxi Yang School of information and control Engineering Qingdao University of TechnologyQingdao 266520China School of Automation and information Engineering Xi’an University of TechnologyXi’an 710048China

In three-dimensional imaging employing phase-shifting profilometry(PSP), the nonlinear response of projector and camera makes the fringe gray distribution non-sinusoidal, which further leads to phase error. Although the double 3-step phaseshifting method is simple and effective, it needs to add an additional set of fringe sequences, which reduces the measurement efficiency. To this end, this paper introduces a generic and flexible self-correction method for nonlinearity-induced phase ***, according to the nonlinearity-induced phase error model, we introduce an additional wrapped phase with a phase difference of π/3. The error waveform of the two wrapped phases is opposite but not coincident. Then, we introduce an estimation algorithm for the additional wrapped phase offset. Finally, we fuse the two wrapped phases to correct the phase error. Experiments confirm that the root mean squared error of the proposed method is 64.1% lower than that of the traditional method and 13.3% lower than that of the Hilbert transform method. The proposed method does not require any additional fringes or hardware assistance and can be easily extended to 4-step or 5-step PSP.

关键词： three-dimensional imaging phase-shifting profilometry nonlinear response self-correction Hilbert transform

An adaptive 3D reconstruction method for asymmetric dual-angle multispectral stereo imaging system on UAV platform

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Science China(information Sciences) 2024年第8期67卷 285-299页

作者： Chen WANG Xian LI Yanfeng GU Zixu WANG School of Electronics and information Engineering Harbin Institute of Technology Beijing inst.tute of control and Electronic technology

A multispectral imaging system often cannot capture 3D spatial information owing to hardware limitations, which diminishes the effectiveness across various domains. To address this problem, we have developed a multispectral stereo imaging system along with an adaptive 3D reconstruction algorithm. Unlike existing unmanned aerial vehicle stereo imaging systems, our multispectral stereo imaging system uses two multispectral cameras with asymmetric spectral bands positioned at different angles. This design enables the acquisition of a higher number of bands and lateral spatial information while maintaining a lightweight structure. This system introduces challenges such as large geometric distortions and intensity differences between multiple bands. To accurately recover 3D spatial information, we propose an adaptive 3D reconstruction method. This method employs a position and orientation system-assisted projection transformation and a normalized threshold adjustment strategy. Finally, mutual information is used to reconstruct the multispectral images densely, effectively addressing nonlinear differences and generating a comprehensive multispectral point cloud. Our stereo system was used for two real data collections in different regions, and the efficacy of the proposed 3D reconstruction method was validated by comparing it with existing methods and commercial software.

关键词： multispectral images 3D reconstruction stereo imaging system unmanned aerial vehicle feature extraction

State estimation for delayed switched positive systems: delayed radius approach

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Science China(information Sciences) 2024年第8期67卷 190-205页

作者： Weizhong CHEN Zhongyang FEI Xudong ZHAO Zheng-Guang WU School of Electronics and information Xi'an Polytechnic University Research inst.tute of Intelligent control and Systems Harbin Institute of Technology Key Laboratory of Intelligent control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of control Science and Engineering Dalian University of Technology State Key Laboratory of Industrial control technology Institute of Cyber-Systems and ControlZhejiang University

In this paper, an interval estimation scheme is developed for delayed switched positive systems（DSPS） with mode-dependent average dwell time switching. A lossless zonotopic estimation approach is proposed for the delayed intersection zonotope with the positive generator matrix. First, considering the existence of asynchronism between the system mode and the correction matrix mode, the mismatched intersection zonotope is constructed for DSPS to verify the consistency between the system model and ***, by utilizing the introduced radius definitions, the ?∞performance is addressed to optimize the size of delayed intersection zonotopes. Subsequently, we present a joint-design approach of switching signals and the mode-dependent correction matrix by constructing positive generator matrix-based delayed radius functions. Furthermore, guaranteed nonnegative state bounds are derived for the considered DSPS based on the proposed lossless zonotopic estimation criteria. Finally, detailed simulations are conducted to validate the feasibility and superiority of the developed methods.

关键词： delayed switched positive systems interval estimation asynchronous correction matrix zonotopes mode-dependent average dwell time

Grouping Decision Algorithm for Dynamic Terminals in Random Access Networks

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Journal of Communications and information Networks 2024年第2期9卷 176-183页

作者： Hongliang Sun Tongfei Chen Chuangye Zhao Mengxin Chen College of information and control Engineering Jilin Institute of Chemical TechnologyJilin 132022China

This paper proposes a grouping decision algorithm for random access networks with the carrier sense multiple access (CSMA) mechanism, which can balance the traffic load and solve the hidden terminal issue. Considering the arrival characteristics of terminals and quality of service (QoS) requirements, the traffic load is evaluated based on the effective bandwidth theory. Additionally, a probability matrix of hidden terminals is constructed to take into account the dynamic nature of hidden terminal relations. In the grouping process, an income function is established with a view to the benefits of decreasing the probability of hidden terminal collisions and load balancing. Then, we introduce the grey wolf optimization (GWO) algorithm to implement the grouping decision. Simulation results demonstrate that the grouping algorithm can effectively alleviate the performance degradation and facilitate the management of network resources.

关键词： random access network hidden terminal collision probability effective bandwidth traffic load grey wolf optimization

Analysis of learnability of a novel hybrid quantum-classical convolutional neural network in image classification

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Chinese Physics B 2024年第4期33卷 275-283页

作者：程涛赵润盛王爽王睿马鸿洋 School of Sciences Qingdao University of TechnologyQingdao 266033China School of information and control Engineering Qingdao University of TechnologyQingdao 266033China

We design a new hybrid quantum-classical convolutional neural network(HQCCNN)model based on parameter quantum *** this model,we use parameterized quantum circuits(PQCs)to redesign the convolutional layer in classical convolutional neural networks,forming a new quantum convolutional layer to achieve unitary transformation of quantum states,enabling the model to more accurately extract hidden information from *** the same time,we combine the classical fully connected layer with PQCs to form a new hybrid quantum-classical fully connected layer to further improve the accuracy of ***,we use the MNIST dataset to test the potential of the *** results indicate that the HQCCNN has good performance in solving classification *** binary classification tasks,the classification accuracy of numbers 5 and 7 is as high as 99.71%.In multivariate classification,the accuracy rate also reaches 98.51%.Finally,we compare the performance of the HQCCNN with other models and find that the HQCCNN has better classification performance and convergence speed.

关键词： parameterized quantum circuits quantum machine learning hybrid quantum-classical convolutional neural network

Design of a novel hybrid quantum deep neural network in INEQR images classification

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Chinese Physics B 2024年第6期33卷 230-238页

作者：王爽王柯涵程涛赵润盛马鸿洋郭帅 School of information and control Engineering Qingdao University of TechnologyQingdao 266033China School of Sciences Qingdao University of TechnologyQingdao 266033China

We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantum circuit, thereby propose a novel hybrid quantum deep neural network(HQDNN) used for image classification. After bilinear interpolation reduces the original image to a suitable size, an improved novel enhanced quantum representation(INEQR) is used to encode it into quantum states as the input of the HQDNN. Multi-layer parameterized quantum circuits are used as the main structure to implement feature extraction and classification. The output results of parameterized quantum circuits are converted into classical data through quantum measurements and then optimized on a classical computer. To verify the performance of the HQDNN, we conduct binary classification and three classification experiments on the MNIST(Modified National inst.tute of Standards and technology) data set. In the first binary classification, the accuracy of 0 and 4 exceeds98%. Then we compare the performance of three classification with other algorithms, the results on two datasets show that the classification accuracy is higher than that of quantum deep neural network and general quantum convolutional neural network.

关键词： quantum computing image classification quantum–classical hybrid neural network quantum image representation interpolation

Decoding topological XYZ^(2) codes with reinforcement learning based on attention mechanisms

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Chinese Physics B 2024年第6期33卷 262-270页

作者：陈庆辉姬宇欣王柯涵马鸿洋纪乃华 School of information and control Engineering Qingdao University of TechnologyQingdao 266033China School of Sciences Qingdao University of TechnologyQingdao 266033China

Quantum error correction, a technique that relies on the principle of redundancy to encode logical information into additional qubits to better protect the system from noise, is necessary to design a viable quantum computer. For this new topological stabilizer code-XYZ^(2) code defined on the cellular lattice, it is implemented on a hexagonal lattice of qubits and it encodes the logical qubits with the help of stabilizer measurements of weight six and weight two. However topological stabilizer codes in cellular lattice quantum systems suffer from the detrimental effects of noise due to interaction with the environment. Several decoding approaches have been proposed to address this problem. Here, we propose the use of a state-attention based reinforcement learning decoder to decode XYZ^(2) codes, which enables the decoder to more accurately focus on the information related to the current decoding position, and the error correction accuracy of our reinforcement learning decoder model under the optimisation conditions can reach 83.27% under the depolarizing noise model, and we have measured thresholds of 0.18856 and 0.19043 for XYZ^(2) codes at code spacing of 3–7 and 7–11, respectively. our study provides directions and ideas for applications of decoding schemes combining reinforcement learning attention mechanisms to other topological quantum error-correcting codes.

关键词： quantum error correction topological quantum stabilizer code reinforcement learning attention mechanism

Quantum generative adversarial networks based on a readout error mitigation method with fault tolerant mechanism

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Chinese Physics B 2024年第4期33卷 285-295页

作者：赵润盛马鸿洋程涛王爽范兴奎 School of Sciences Qingdao University of TechnologyQingdao 266033China School of information and control Engineering Qingdao University of TechnologyQingdao 266033China

Readout errors caused by measurement noise are a significant source of errors in quantum circuits,which severely affect the output results and are an urgent problem to be solved in noisy-intermediate scale quantum(NISQ)*** this paper,we use the bit-flip averaging(BFA)method to mitigate frequent readout errors in quantum generative adversarial networks(QGAN)for image generation,which simplifies the response matrix structure by averaging the qubits for each random bit-flip in advance,successfully solving problems with high cost of measurement for traditional error mitigation *** experiments were simulated in Qiskit using the handwritten digit image recognition dataset under the BFA-based method,the Kullback-Leibler(KL)divergence of the generated images converges to 0.04,0.05,and 0.1 for readout error probabilities of p=0.01,p=0.05,and p=0.1,***,by evaluating the fidelity of the quantum states representing the images,we observe average fidelity values of 0.97,0.96,and 0.95 for the three readout error probabilities,*** results demonstrate the robustness of the model in mitigating readout errors and provide a highly fault tolerant mechanism for image generation models.

关键词： readout errors quantum generative adversarial networks bit-flip averaging method fault tolerant mechanisms

Recurrent neural network decoding of rotated surface codes based on distributed strategy

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Chinese Physics B 2024年第4期33卷 322-330页

作者：李帆李熬庆甘启迪马鸿洋 School of information and control Engineering Qingdao University of TechnologyQingdao 266033China School of Sciences Qingdao University of TechnologyQingdao 266033China

Quantum error correction is a crucial technology for realizing quantum *** computers achieve faulttolerant quantum computing by detecting and correcting errors using decoding *** error correction using neural network-based machine learning methods is a promising approach that is adapted to physical systems without the need to build noise *** this paper,we use a distributed decoding strategy,which effectively alleviates the problem of exponential growth of the training set required for neural networks as the code distance of quantum error-correcting codes *** decoding algorithm is based on renormalization group decoding and recurrent neural network *** recurrent neural network is trained through the ResNet architecture to improve its decoding *** we test the decoding performance of our distributed strategy decoder,recurrent neural network decoder,and the classic minimum weight perfect matching(MWPM)decoder for rotated surface codes with different code distances under the circuit noise model,the thresholds of these three decoders are about 0.0052,0.0051,and 0.0049,*** results demonstrate that the distributed strategy decoder outperforms the other two decoders,achieving approximately a 5%improvement in decoding efficiency compared to the MWPM decoder and approximately a 2%improvement compared to the recurrent neural network decoder.

关键词： quantum error correction rotated surface code recurrent neural network distributed strategy