Volume 47 Issue 11 • Nov. 2017
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Table of contents
Publication Year: 2017, Page(s):C1 - 3481|
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IEEE Transactions on Cybernetics
Publication Year: 2017, Page(s): C2|
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Controllability and Synchronization Analysis of Identical-Hierarchy Mixed-Valued Logical Control Networks
Publication Year: 2017, Page(s):3482 - 3493
Cited by: Papers (10)This paper investigates the controllability and synchronization problems for identical-hierarchy mixed-valued logical control networks. The logical network considered is hierarchical, and Boolean network is a special case of logical network. Here, identical-hierarchy means that there are identical number of nodes in each layer of logical network and corresponding nodes have the same dimension for ... View full abstract»
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A New Deformation Model of Biological Tissue for Surgery Simulation
Publication Year: 2017, Page(s):3494 - 3503
Cited by: Papers (4)A novel meshless deformation model of biological soft tissue, which is mainly based on the radial basis function point interpolation, is presented for interactive simulation applications such as virtual surgery simulators. Compared with conventional mesh models, the proposed model is particularly suitable for simulating large deformation, sucking and cutting tasks since there is no need to maintai... View full abstract»
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Reference Adaptation for Robots in Physical Interactions With Unknown Environments
Publication Year: 2017, Page(s):3504 - 3515
Cited by: Papers (1)In this paper, we propose a method of reference adaptation for robots in physical interactions with unknown environments. A cost function is constructed to describe the interaction performance, which combines trajectory tracking error and interaction force between the robot and the environment. It is minimized by the proposed reference adaptation based on trajectory parametrization and iterative l... View full abstract»
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Low-Rank Discriminant Embedding for Multiview Learning
Publication Year: 2017, Page(s):3516 - 3529
Cited by: Papers (6)This paper focuses on the specific problem of multiview learning where samples have the same feature set but different probability distributions, e.g., different viewpoints or different modalities. Since samples lying in different distributions cannot be compared directly, this paper aims to learn a latent subspace shared by multiple views assuming that the input views are generated from this late... View full abstract»
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Person Reidentification in a Distributed Camera Network Framework
Publication Year: 2017, Page(s):3530 - 3541
Cited by: Papers (4)Plenty of research has been conducted to obtain the best reidentification performance between a single camera-pairs. None of the current approaches has addressed the reidentification in a camera network by considering the network topology (i.e., the structure of the monitored environment). We introduce a distributed network person reidentification framework which introduces the following contribut... View full abstract»
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Active Complementary Control for Affine Nonlinear Control Systems With Actuator Faults
Publication Year: 2017, Page(s):3542 - 3553
Cited by: Papers (3)This paper is concerned with the problem of active complementary control design for affine nonlinear control systems with actuator faults. The outage and loss of effectiveness fault cases are considered. In order to achieve the performance enhancement of the faulty control system, the complementary control scheme is designed in two steps. Firstly, a novel fault estimation scheme is developed. Then... View full abstract»
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Distribution-Based Cluster Structure Selection
Publication Year: 2017, Page(s):3554 - 3567
Cited by: Papers (12)The objective of cluster structure ensemble is to find a unified cluster structure from multiple cluster structures obtained from different datasets. Unfortunately, not all the cluster structures contribute to the unified cluster structure. This paper investigates the problem of how to select the suitable cluster structures in the ensemble which will be summarized to a more representative cluster ... View full abstract»
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Group-Based Alternating Direction Method of Multipliers for Distributed Linear Classification
Publication Year: 2017, Page(s):3568 - 3582
Cited by: Papers (1)The alternating direction method of multipliers (ADMM) algorithm has been widely employed for distributed machine learning tasks. However, it suffers from several limitations, e.g., a relative low convergence speed, and an expensive time cost. To this end, in this paper, a novel method, namely the group-based ADMM (GADMM), is proposed for distributed linear classification. In particular, to accele... View full abstract»
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Automatic Subspace Learning via Principal Coefficients Embedding
Publication Year: 2017, Page(s):3583 - 3596
Cited by: Papers (33)In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i.e., automatic subspace learning) and 2) how to learn the underlying subspace in the presence of Gaussian noise (i.e., robust subspace learning). We show that these two problems can be simultaneously solved by proposing a new method ... View full abstract»
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Statistical Hypothesis Detector for Abnormal Event Detection in Crowded Scenes
Publication Year: 2017, Page(s):3597 - 3608
Cited by: Papers (4)Abnormal event detection is now a challenging task, especially for crowded scenes. Many existing methods learn a normal event model in the training phase, and events which cannot be well represented are treated as abnormalities. However, they fail to make use of abnormal event patterns, which are elements to comprise abnormal events. Moreover, normal patterns in testing videos may be divergent fro... View full abstract»
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Hazard Detection for Motorcycles via Accelerometers: A Self-Organizing Map Approach
Publication Year: 2017, Page(s):3609 - 3620
Cited by: Papers (2)This paper deals with collision and hazard detection for motorcycles via inertial measurements. For this kind of vehicles, the most difficult challenge is to distinguish road's anomalies from real hazards. This is usually done by setting absolute thresholds on the accelerometer measurements. These thresholds are heuristically tuned from expensive crash tests. This empirical method is expensive and... View full abstract»
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Adaptive Control of Semi-Autonomous Teleoperation System With Asymmetric Time-Varying Delays and Input Uncertainties
Publication Year: 2017, Page(s):3621 - 3633
Cited by: Papers (4)This paper addresses the adaptive task-space bilateral teleoperation for heterogeneous master and slave robots to guarantee stability and tracking performance, where a novel semi-autonomous teleoperation framework is developed to ensure the safety and enhance the efficiency of the robot in remote site. The basic idea is to stabilize the tracking error in task space while enhancing the efficiency o... View full abstract»
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Generalized Hybrid Constructive Learning Algorithm for Multioutput RBF Networks
Publication Year: 2017, Page(s):3634 - 3648
Cited by: Papers (1)An efficient generalized hybrid constructive (GHC) learning algorithm for multioutput radial basis function (RBF) networks is proposed to obtain a compact network with good generalization capability. By this algorithm, one can train the adjustable parameters and determine the optimal network structure simultaneously. First, an initialization method based on the growing and pruning algorithm is uti... View full abstract»
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Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method
Publication Year: 2017, Page(s):3649 - 3657
Cited by: Papers (29)Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve t... View full abstract»
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TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds
Publication Year: 2017, Page(s):3658 - 3668
Cited by: Papers (16)The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studie... View full abstract»
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Sliding Mode Control for Discrete-Time Systems With Markovian Packet Dropouts
Publication Year: 2017, Page(s):3669 - 3679
Cited by: Papers (1)This paper presents the design of a sliding mode controller for networked control systems subject to successive Markovian packet dropouts. This paper adopts the Gilbert-Elliott channel model to describe the temporal correlation among packet losses, and proposes an update scheme to select the assumed available states for use in a sliding mode control law. A technique used in the theory of discrete-... View full abstract»
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Multiview Physician-Specific Attributes Fusion for Health Seeking
Publication Year: 2017, Page(s):3680 - 3691
Cited by: Papers (1)Community-based health services have risen as important online resources for resolving users health concerns. Despite the value, the gap between what health seekers with specific health needs and what busy physicians with specific attitudes and expertise can offer is being widened. To bridge this gap, we present a question routing scheme that is able to connect health seekers to the right physicia... View full abstract»
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A Concurrent Multiple Negotiation Protocol Based on Colored Petri Nets
Publication Year: 2017, Page(s):3692 - 3705
Cited by: Papers (2)Concurrent multiple negotiation (CMN) provides a mechanism for an agent to simultaneously conduct more than one negotiation. There may exist different interdependency relationships among these negotiations and these interdependency relationships can impact the outcomes of these negotiations. The outcomes of these concurrent negotiations contribute together for the agent to achieve an overall negot... View full abstract»
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Dynamically Modulated Mask Sparse Tracking
Publication Year: 2017, Page(s):3706 - 3718
Cited by: Papers (7)Visual tracking is a critical task in many computer vision applications such as surveillance and robotics. However, although the robustness to local corruptions has been improved, prevailing trackers are still sensitive to large scale corruptions, such as occlusions and illumination variations. In this paper, we propose a novel robust object tracking technique depends on subspace learning-based ap... View full abstract»
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A Semi-Supervised Method for Surveillance-Based Visual Location Recognition
Publication Year: 2017, Page(s):3719 - 3732
Cited by: Papers (2)In this paper, we are devoted to solving the problem of crossing surveillance and mobile phone visual location recognition, especially for the case that the query and reference images are captured by mobile phone and surveillance camera, respectively. Besides, we also study the influence of the environmental condition variations on this problem. To explore that problem, we first build a cross-devi... View full abstract»
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Rotational Invariant Dimensionality Reduction Algorithms
Publication Year: 2017, Page(s):3733 - 3746
Cited by: Papers (11)A common intrinsic limitation of the traditional subspace learning methods is the sensitivity to the outliers and the image variations of the object since they use the L<sub>2</sub> norm as the metric. In this paper, a series of methods based on the L<sub>2,1</sub>-norm are proposed for linear dimensionality reduction. Since the L<sub>2,1</sub>-norm based object... View full abstract»
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Adaptive NN Control Using Integral Barrier Lyapunov Functionals for Uncertain Nonlinear Block-Triangular Constraint Systems
Publication Year: 2017, Page(s):3747 - 3757
Cited by: Papers (6)A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of... View full abstract»
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Discriminative Dictionary Learning With Two-Level Low Rank and Group Sparse Decomposition for Image Classification
Publication Year: 2017, Page(s):3758 - 3771
Cited by: Papers (8)Discriminative dictionary learning (DDL) framework has been widely used in image classification which aims to learn some class-specific feature vectors as well as a representative dictionary according to a set of labeled training samples. However, interclass similarities and intraclass variances among input samples and learned features will generally weaken the representability of dictionary and t... View full abstract»
Aims & Scope
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics.
Meet Our Editors
Editor-in-Chief
Prof. Jun Wang
Dept. of Computer Science
City University of Hong Kong
Kowloon Tong, Kowloon, Hong Kong
Tel: +852 34429701
Email: jwang.cs@cityu.edu.hk