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[转载]【当期目录】IEEE/CAA JAS 第9卷 第8期

已有 626 次阅读 2022-9-13 10:10 |个人分类:博客资讯|系统分类:博客资讯|文章来源:转载

【当期目录】IEEE/CAA JAS 第9卷 第8期


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AI,复杂网络,自然语言处理,深度学习,神经网络,多智能体系统,机器人,迭代控制...


全球科研机构

美国Florida Atlantic University;英国University of Portsmouth;新加坡Nanyang Technological University、Institute for Infocomm Research, Agency for Science, Technology and Research;西班牙University of Granada;日本University of Toyama;荷兰Eindhoven University of Technology;清华大学、中科院数学与系统科学研究院、北京航空航天大学、电子科技大学、中国科学技术大学、华中科技大学...


Y. Ming, N. N. Hu, C. X. Fan, F. Feng, J. W. Zhou, and  H. Yu,  “Visuals to text : A comprehensive review on automatic image captioning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1339–1365, Aug. 2022. doi: 10.1109/JAS.2022.105734

> Conducting a comprehensive review of image captioning, covering both traditional methods and recent deep learning-based techniques, as well as the publicly available datasets, evaluation metrics, the open issues and challenges.

> Focusing on the deep learning-based image captioning researches, which is categorized into the encoder-decoder framework, attention mechanism and training strategies on the basis of model structures and training manners for a detailed introduction.

> Discussing several future research directions of image captioning, such as Flexible Captioning, Unpaired Captioning, Paragraph Captioning and Non-Autoregressive Captioning.


J. H. Lü, G. H. Wen, R. Q. Lu, Y. Wang, and  S. M. Zhang,  “Networked knowledge and complex networks: An engineering view,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1366–1383, Aug. 2022. doi: 10.1109/JAS.2022.105737

> State-of-the-art advances of complex networks and deep learning were briefly reviewed.

> A new framework of networked knowledge was suggested from the perspective of complex networks.

> Deep learning technologies for networked knowledge were reviewed and analyzed.


S. W. Wang, X. Q. Zhu, W. P. Ding, and  A. A. Yengejeh,  “Cyberbullying and cyberviolence detection: A triangular user-activity-content view,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1384–1405, Aug. 2022. doi: 10.1109/JAS.2022.105740

> A comprehensive review of computational approaches for cyberbullying and cyberviolence detection.

> A UAC triangle view of the key factors in cyberbullying.

> Important features and their interactions in cyberbullying detection.


C. Y. Lee, H. Hasegawa, and  S. C. Gao,  “Complex-valued neural networks: A comprehensive survey,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1406–1426, Aug. 2022. doi: 10.1109/JAS.2022.105743

> A comprehensive collection of variants of CVNNs are presented to provide their various structures.

> A systematic categorization of the recent applications of CVNNs provides an easy reference.

> Future research prospective on CVNNs are discussed.


R. B. Jin, M. Wu, K. Y. Wu, K. Z. Gao, Z. H. Chen, and  X. L. Li,  “Position encoding based convolutional neural networks for machine remaining useful life prediction,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1427–1439, Aug. 2022. doi: 10.1109/JAS.2022.105746

> A new convolutional neural network is proposed for machine remaining useful life prediction.

> A series of important principles are developed for enhancing the performance of CNNs on the RUL prediction.

> A novel position encoding scheme is proposed for the RUL prediction.


Y. M. Ju, D. R. Ding, X. He, Q.-L. Han, and G. L. Wei, “Consensus control of multi-agent systems using fault-estimation-in-the-loop: Dynamic event-triggered case,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1440–1451, Aug. 2022. doi: 10.1109/JAS.2021.1004386

> Proposed a novel consensus control framework with fault-estimation-in-the-loop for the MASs under DETP.

> Desired estimator and controller gains have been obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way, respectively.

> A simulation result has been provided to verify the effectiveness of the proposed approach.


M. Liu, X. Y. Zhang, M. S. Shang, and  L. Jin,  “Gradient-based differential kWTA network with application to competitive coordination of multiple robots,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1452–1463, Aug. 2022. doi: 10.1109/JAS.2022.105731

> A novel GD-kWTA network is designed, which is equipped with improved accuracy and enhanced robustness in tackling kWTA operations.

> Theorems on the convergence and robustness of the proposed network and numerical simulations in cases with or without noises are presented.

> Aided with the constructed GD-kWTA network for describing the competitive behavior, an application on the multirobot system for conducting the tracking task is provided.


L. Chen, Z. Lin, H. Garcia de Marina, Z. Sun, and  M. Feroskhan,  “Maneuvering angle rigid formations with global convergence guarantees,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1464–1475, Aug. 2022. doi: 10.1109/JAS.2022.105749

> Aims to solve this challenging problem in both 2D and 3D under a leader-follower framework.

> Proposed angle-constrained formation maneuvering laws enable the maneuvering motions of simultaneous translation, rotation and scaling.

> Proposed 2D and 3D angle-constrained formation maneuvering laws have global convergence guarantee.


S. F. Han, K. Zhu, M. C. Zhou, X. J. Liu, H. Y. Liu, Y. Al-Turki, and A. Abusorrah, “A novel multiobjective fireworks algorithm and its applications to imbalanced distance minimization problems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1476–1489, Aug. 2022. doi: 10.1109/JAS.2022.105752

> A new multiobjective fireworks algorithm is proposed.

> A special archive for each firework is established to guide firework explosion.

> An adaptive strategy is designed to ensure fast convergence and high solution diversity in decision space.


L. Z. Wang, G. Xie, F. C. Qian, J. Liu, and  K. Zhang,  “A novel PDF shape control approach for nonlinear stochastic systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1490–1498, Aug. 2022. doi: 10.1109/JAS.2022.105755

> Proposed method is suitable for any nonlinear stochastic system.

> Approach is more accurate and dependable than other approximate methods.

> Can make the PDF of state response match different target PDFs.


S. R. Nekoo, J. Á. Acosta, G. Heredia, and  A. Ollero,  “A PD-type state-dependent Riccati equation with iterative learning augmentation for mechanical systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1499–1511, Aug. 2022. doi: 10.1109/JAS.2022.105533

> A nonlinear finite-time PD-like controller is presented based on SDDRE augmented with ILC.

> A convex objective function is introduced for regulation training rule of gradient descent.

> Uniform boundedness in finite time is guaranteed, suitable for unstable mechanical systems.


L. L. Chen, L. Shi, Q. Zhou, H. M. Sheng, and Y. H. Cheng, “Secure bipartite tracking control for linear leader-following multiagent systems under denial-of-service attacks,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1512–1515, Aug. 2022. doi: 10.1109/JAS.2022.105758


K. Zhang, Y. Liu, and J. B. Tan, “Finite-time stabilization of linear systems with input constraints by event-triggered control,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1516–1519, Aug. 2022. doi: 10.1109/JAS.2022.105761


T. Liu, M. W. Hu, S. N. Ma, Y. Xiao, Y. Liu, and W. T. Song, “Exploring the effectiveness of gesture interaction in driver assistance systems via virtual reality,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1520–1523, Aug. 2022. doi: 10.1109/JAS.2022.105764


C. L. Peng and J. Y. Ma, “Domain adaptive semantic segmentation via entropy-ranking and uncertain learning-based self-training,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1524–1527, Aug. 2022. doi: 10.1109/JAS.2022.105767


Y. Liu, Y. Shi, F. H. Mu, J. Cheng, and X. Chen, “Glioma segmentation-oriented multi-modal MR image fusion with adversarial learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1528–1531, Aug. 2022. doi: 10.1109/JAS.2022.105770


Q. M. Cheng, Y. Z. Zhou, H. Y. Huang, and Z. Y. Wang, “Multi-attention fusion and fine-grained alignment for bidirectional image-sentence retrieval in remote sensing,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1532–1535, Aug. 2022. doi: 10.1109/JAS.2022.105773


S. Zhang, L. Tang, and Y.-J. Liu, “Estimation based adaptive constraint control for a class of coupled string systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1536–1539, Aug. 2022. doi: 10.1109/JAS.2022.105776


Y. J. Wang, K. Q. Li, and Z. H. Chen, “Battery full life cycle management and health prognosis based on cloud service and broad learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1540–1542, Aug. 2022. doi: 10.1109/JAS.2022.105779




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