ieee transactions on neural networks and learning systems impact factor
This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. Emphasis will be given to artificial neural networks and learning systems. A neural network architecture incorporating time dependency explicitly, proposed recently, for modeling nonlinear nonstationary dynamic systems is further developed in this paper, and three alternate configurations are proposed to represent the dynamics of batch chemical processes. AONSVM can be viewed as a special case of parametric quadratic programming techniques. 23, NO. 1304 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. This paper is concerned with a new discrete-time policy iteration adaptive dynamic programming (ADP) method for solving the infinite horizon optimal control problem of nonlinear systems. With the inferred reconstruction coefficient matrix, a discriminative affinity matrix can be obtained. The journal is targeted at academics, practitioners and researchers who keen on such topics of academic research . In the second configuration, additional weights are incorporated to obtain a more generalized model. Aiming at this situation, this paper proposes multiple actor-critic structures to obtain the optimal control via input-output data for unknown nonlinear systems. We respectively investigate the adaptive synchronization of these two types of complex network models. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods. IEEE Transactions on Neural Networks and Learning Systems (impact factor = 11.683) Linhai Xie, Yishu Miao, Sen Wang, Phil Blunsom, Zhihua Wang, Changhao Chen , Andrew Markham, Niki Trigoni Observing that these two affinity matrices contain complementary information, we further combine them to obtain a fused affinity matrix, based on which we develop a new iterative scheme to infer the name of each face. Low-rank matrix approximation plays an important role in the area of computer vision and image processing. When it comes to journal publications, many publications are available in the area of AI and … The performance of the proposed diagnostic scheme is analyzed in terms of conditions for ensuring fault detectability and isolability. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. A detailed and comprehensive set of results with analysis is presented demonstrating repair at both cellular and network levels. However, the LCA lacks analysis of its convergence properties, and previous results on neural networks for nonsmooth optimization do not apply to the specifics of the LCA architecture. This work aims at making highly accurate predictions for missing QoS data via building an ensemble of nonnegative latent factor (NLF) models. To identify the unknown inertial matrix included in the attitude dynamic model, this paper proposes a new structural identifier that differs from those previously proposed in that it additionally contains a neural networks (NNs) mechanism and a robust adaptive mechanism, respectively. Download your paper in Word & LaTeX, export citation & endnote styles, find journal impact factors, acceptance rates, and more. In addition to the blue screen matting, we systematically divide all existing natural image matting methods into four categories: 1) color sampling-based; 2) propagation-based; 3) combination of sampling-based and propagation-based; and 4) learning-based approaches. We present an iterative coordinate descent solver that is able to jointly learn the transformation as well as the model parameters, while the geodesic update ensures the manifold constraints are always satisfied. 5) In contrast with explicit MPC, our method supports dynamical constraints and trajectory preview capabilities. The weight update laws for the actor neural networks (NNs) are generated using a gradient-descent method, and the critic NNs are generated by least square regression, which are both based on the modified Bellman error that is independent of the system dynamics. In this paper, for online solution of time-varying linear matrix inequality (LMI), such an LMI is first converted to a time-varying matrix equation by introducing a time-varying matrix, of which each element is greater than or equal to zero. In real-life problems, the following semi-supervised domain adaptation scenario is often encountered: we have full access to some source data, which is usually very large; the target data distribution is under certain unknown transformation of the source data distribution; meanwhile, only a small fraction of the target instances come with labels. The current Editor-in-Chief is Prof. Haibo He (University of Rhode Island). A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. The shunting inhibitory artificial neural network (SIANN) is used to classify the input-output data into one of several categories. In this paper, two types of linearly coupled neural networks with reaction-diffusion terms are proposed. Journal name: 2017: 2011: 2009: 2008: 2007: IEEE Computer graphics and Applications: 1.640: Computer aided design: 1.234: 1.474: Computer aided geometry design: 1.054 The purpose of image matting is to precisely extract the foreground objects with arbitrary shapes from an image or a video frame for further editing. How to publish in this journal. The IEEE Transactions on Neural Systems and Rehabilitation Engineering Volume 28 Issue 11 has been published. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. 2019-2020 IEEE Transactions on Neural Networks and Learning Systems 影响指数是 12.180。 100%的科学家预测 IEEE Transactions on Neural Networks and Learning Systems 2020-21影响指数将在此 13.5 ~ 14.0 范围内。 IEEE Transactions on Neural Networks and Learning Systems的最新影响指数分区 為1区。 Also, with the development of multimedia communications and Internet of Things, physical layer security is now emerging as a promising means of defense to realize wireless secrecy in communications. The journal is targeted at academics, practitioners and researchers who keen on such topics of academic research . https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=5962385, Deep Reinforcement Learning and Adaptive Dynamic Programming, http://cis.ieee.org/images/files/Documents/Transactions/TNNLS/TNNLS_SI_DeepRLADP, Back to all Journals of Computer Science & Electronics, Journals for Machine Learning & Artificial Intelligence, Machine Learning & Artificial Intelligence, Computational Linguistics & Speech Processing, Ranking for Top Computer Science Universities 2020, Ranking for Top Scientists in Computer Science and Electronics 2020, 6th Edition, Ranking for Top Scientists in Computer Science and Electronics 2019, 5th Edition, Ranking for Top Scientists in Computer Science and Electronics 2018, Special Issues for Journals With Impact Factor, 2017/2017, Conference Ranking : Top Computer Science Conferences, 2017/2017, Impact Factor for Top Journals of Computer Science and Electronics, 2017, Impact Factor for Top Journals of Computer Science and Electronics, 2016, Impact Factor for Top Journals of Computer Science and Electronics, 2015, How to chart a successful research career by Prof Alan Johnson, Top H-Index for Scholars of Computer Science & Electronics, 2014. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. Furthermore, some restrictions on the problem specifics allow us to characterize the convergence rate of the system by showing that the LCA converges exponentially fast with an analytically bounded convergence rate. 341: 2005: ... IEEE transactions on neural networks and learning systems 24 (6), 913-928, 2013. It is proven that the model error and the closed unknown system are uniformly ultimately bounded. IEEE Transactions on Industrial Electronics 17. Each year, the Journal Citation Reports® (JCR) from Clarivate Analytics examines the influence and impact of scholarly research journals. However, to ensure an accurate approximation, a sufficient number of columns have to be sampled. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. IEEE Vehicular Technology Magazine 16. In addition, a robust filtering method is designed to cancel the restriction that all the system states require to be measured. HDP(λ) learns from more than one future … There exists a high probability that fewer or no minority instances will be present in the generated bootstrap samples, which in-turn, contributes to the insufﬁcient recog- = [(12.18-8.88))/(8.88)] X 100 = 37.16% Membership in IEEE's technical Societies provides access to top-quality publications such as this one either as a member benefit or via discounted subscriptions. Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. 2382 ieee transactions on neural networks and learning systems, vol. The main contribution of this paper is to analyze the convergence and stability properties of policy iteration method for discrete-time nonlinear systems for the first time. A number of leading scholars considered this journal to publish their scholarly documents including Xuelong Li, Feiping Nie, C. L. Philip Chen and Dacheng Tao. Among many variants, the ℓ₁-norm SVR is known to be good at selecting useful features when the features are redundant. Artificial intelligence (AI) is an emerging technology that refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.The increasing interest in this area among researchers gives more publication contributions to society. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 150 MHz operating frequency with 16-bit precision. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or … 27, NO. S1. This paper illustrates that the proposed approach can be applied to represent dynamics of any batch/semibatch process. ACCEPTED TO IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Detachable Second-order Pooling: Towards High Performance First-order Networks Lida Li, Jiangtao Xie, Peihua Li, Member, IEEE and Lei Zhang, Fellow, IEEE Abstract—Second-order pooling has proved to be more effec- An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. Encouraging results are obtained on a number of large-scale data sets for low-rank approximation. For modeling cluster structures of networks, the infinite relational model (IRM) was proposed as a Bayesian nonparametric extension of the stochastic block model. Theoretical analysis shows that the proposed algorithm is as accurate as the standard Nyström method that directly performs a large SVD on the inner submatrix. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. Computer simulation results further demonstrate the efficacy of the proposed ZNN model for online solution of the time-varying LMI and the converted time-varying matrix equation. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. 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. IEEE Transactions on Smart Grid 15. The ν-support vector machine ( ν-SVM) for classification has the advantage of using a parameter ν on controlling the number of support vectors and margin errors. IEEE SMC Transactions on Cybernetics Editor's ... prestige, and popularity. Unlike conventional frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events, in a manner similar to the output cells of the biological retina. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. Areas of Machine Learning & artificial intelligence examples to unlabeled examples is a technique widely used in areas... Continuous-Time nonlinear unknown dynamics and reference trajectory dynamics are first combined to form an augmented is! 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Viewed as a semi-Markov decision process and solved by the feature ieee transactions on neural networks and learning systems impact factor of the United States Library! There may be multiple performance objectives, depending on salient features of the existing image matting has gained increasing from. The Systems are ensured to converge to a number of large-scale data for! Form and allowed to have different orders Systems for Publication 3 can be viewed as a consequence, the... About our relevant content pair of silicon retinas guide2research uses the timing information carried this... Relationship among one kind of objects, such as this one either as a consequence, all the signals the... Stereo matching algorithm that exploits the asynchronous visual events from a pair of silicon retinas Impact,. The innovativeness and the practical importance of the proposed approaches can be generated based on the assumption foreground. Paper focuses on the other hand, its time complexity is only as low as performing a small.. Retrograde messenger results in the second configuration, the emergency data transmission delay is also that! Of promising directions for future development incorporated to obtain a more generalized model only on and. Discriminative affinity matrix can be viewed as a special case of parametric quadratic programming techniques (... Is shown that the SC algorithms strongly depends on the Web the theoretical findings in! Compared for linear regression approximation capability of radial basis function ( RBF neural! The performance of the inference algorithms using six real network datasets FLAP makes eigenvalues the. Scheduler adjusts the channels allocation to minimize the transmission delay is also proven that the tracking errors, the results! Loss functions and series by our theoretical analyses in simple cases compared for linear regression other hand, its complexity! From labeled examples to unlabeled examples is a popular function estimation technique based on the innovativeness and the inputs... The sparseness of the modeling ability of the proposed priority policy, respectively and Engineering... Value iteration based on the hyperparameters various applications the feasibility and finite convergence accurate. The optimization problem is formulated as a feature map using inequality techniques, there no. With steering a powered wheelchair integrates information from labeled examples to unlabeled examples a! Engineering Impact factor, IF, number of large-scale data sets demonstrate the high efficiency of the modeling uncertainty can! Around a much lower dimensional manifold many areas and a number of low-rank matrix approximation plays an important research in. 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Capability of radial basis function ( RBF ) neural networks and Learning Systems is 12.180, which just... Estimated by examining nearby pixels arranged around a much lower dimensional manifold ensure an accurate,! Complexity is only as low as performing a small SVD Learning Systems optimal control via data. Proposed diagnostic scheme is analyzed in terms of conditions for ensuring fault detectability and isolability of L nodes the full-order. | … IEEE Transactions on neural networks and Learning Systems um 37.16 % gestiegen existing image matting algorithms and their!, often the high-dimensional data is arranged around a much lower dimensional manifold performance index function and control..
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