Xiao-Jian Li, Guang-Hong Yang: Adaptive Fault-Tolerant Synchronization Control of a Class of Complex Dynamical Networks With General Input Distribution Matrices and Actuator Fault This paper presents a generic framework and specific techniques to detect when a process changes and to localize the parts of the process that have changed. on Circuits and Systems for Video Technology, IEEE Trans. We have set-up a special Fast-Track under IEEE TNNLS to process COVID-19 focused manuscripts. Here are the important information: We look forward to your submissions and support to TNNLS! In addition, both algorithms can be further extended for the minimization of the expected symmetric loss. Haibo He. 7, JULY 2012 SSC: A Classifier Combination Method Based on Signal Strength Haibo He, Senior Member, IEEE, and Yuan Cao, Student Member, IEEE Abstract—We propose a new classifier combination method, the signal strength-based combining (SSC) approach, to combine the outputs of multiple classifiers to … Submission Deadline: March 12, 2021. However, until now there were no effective algorithms proposed to address incremental SVOR learning due to the complicated formulations of SVOR. The trajectories of the internal reinforcement signal nonlinear system are considered as the first case. ... Haibo He… In this paper, we prove its uniformly ultimately bounded (UUB) property under certain conditions. In this paper, we propose a novel neural network architecture called Mode-Adaptive Neural Networks for controlling quadruped characters. It covers the theory, design, and applications of neural networks and related learning systems. BibTeX @MISC{Zhong_thisarticle, author = {Xiangnan Zhong and Haibo He and Senior Member and Huaguang Zhang and Senior Member and Zhanshan Wang}, title = {This article has been accepted for inclusion in a future issue of this journal. Browse all the issues of IEEE Transactions on Neural Networks and Learning Systems ... Browse all the issues of IEEE Transactions on Neural Networks and Learning Systems | IEEE Xplore IEEE websites place cookies on your device to give you the best user experience. PREPRINT SUBMITTED TO IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Active Dictionary Learning in Sparse Representation Based Classification Jin Xu, Haibo He, Senior Member, IEEE, and Hong Man, Senior Member, IEEE Abstract—Sparse representation, which uses dictionary atoms to reconstruct input vectors, has been studied intensively in recent years. On testing, the prediction paths of a given test example may be required to end at leaf nodes of the label hierarchy. Cited by. By using Lyapunov stability, we demonstrate the boundedness of the estimated error for the critic and actor neural networks as well as learning rate parameters. 2: The framework of the proposed Deep Dictionary Learning and Coding Network (DDLCN). The IEEE Transactions on Neural Networks and Learning Systems is primarily devoted to archival reports of work that have not been published elsewhere. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., ...". IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. Index Terms — Bayesian decision, hierarchical classification, integer linear program (ILP), multilabel classification. 1100 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. Bibliographic content of IEEE Transactions on Neural Networks and Learning Systems, Volume 24 ... IEEE Transactions on Neural Networks and Learning Systems, Volume 24 ... Haibo He, Jinyu Wen: Adaptive Learning in Tracking Control Based on the Dual Critic Network … Sort by citations Sort by year Sort by title. 2, FEBRUARY 2015 367 A Parametric Classification Rule Based on the Exponentially Embedded Family Bo Tang, Student Member, IEEE, Haibo He, Senior Member, IEEE, Quan Ding, Member, IEEE, and Steven Kay, Fellow, IEEE … From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. ... Haibo He … Xiangnan Zhong, Haibo He, Senior Member, Huaguang Zhang, Senior Member, Zhanshan Wang, by Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal con-trol approa ...", to validate the performance of the proposed optimal control method. 601-613 Index Terms — Adaptive dynamic programming (ADP), Markov jump, "... Abstract — Deep machine learning (DML) holds the potential to revolutionize machine learning by automating rich feature extraction, which has become the primary bottleneck of human engineering in pattern recognition systems. JCR reveals the relationship between citing and cited journals, offering a systematic, objective means to evaluate the world's leading journals. 7, JULY 2012 SSC: A Classifier Combination Method Based on Signal Strength Haibo He, Senior Member, IEEE, and Yuan Cao, Student Member, IEEE … an intrinsic property rather than the … IEEE Transactions on Neural Networks and Learning Systems. The IEEE Transactions on Neural Networks and Learning Systems publishes technical articles that deal with the theory, design, and applications of neural networks and related learning systems. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information. 2, FEBRUARY 2015 367 A Parametric Classification Rule Based on the Exponentially Embedded Family Bo Tang, Student Member, IEEE, Haibo He, Senior Member, IEEE, Quan Ding, Member, IEEE, and Steven Kay, Fellow, IEEE Abstract—In this paper, we extend the exponentially embedded family (EEF), a new approach to … Eligibility traces have long been popular in Q-learning. The IEEE Transactions on Neural Networks and Learning Systems publishes technical articles that deal with the theory, design, and applications of neural networks and related learning systems. The majority of the schemes p ...", Abstract — Catastrophic forgetting is a well-studied attribute of most parameterized supervised, "... Abstract — Conditional random fields (CRF) and structural support vector machines (structural SVM) are two state-of-theart methods for structured prediction that captures the interdependencies among output variables. 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