# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 25 of 27

Publication Year: 2017, Page(s):C1 - 269
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• ### IEEE Transactions on Cybernetics

Publication Year: 2017, Page(s): C2
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• ### Norm Monitoring Under Partial Action Observability

Publication Year: 2017, Page(s):270 - 282
Cited by:  Papers (1)
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In the context of using norms for controlling multiagent systems, a vitally important question that has not yet been addressed in the literature is the development of mechanisms for monitoring norm compliance under partial action observability. This paper proposes the reconstruction of unobserved actions to tackle this problem. In particular, we formalize the problem of reconstructing unobserved a... View full abstract»

• ### Real-Time Fault Detection Approach for Nonlinear Systems and its Asynchronous T–S Fuzzy Observer-Based Implementation

Publication Year: 2017, Page(s):283 - 294
Cited by:  Papers (32)
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This paper is concerned with a real-time observer-based fault detection (FD) approach for a general type of nonlinear systems in the presence of external disturbances. To this end, in the first part of this paper, we deal with the definition and the design condition for an £∞/£2type of nonlinear observer-based FD systems. This analytical framework is fundamental for the devel... View full abstract»

• ### Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics

Publication Year: 2017, Page(s):295 - 305
Cited by:  Papers (10)
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This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is i... View full abstract»

• ### Adjustable Parameter-Based Distributed Fault Estimation Observer Design for Multiagent Systems With Directed Graphs

Publication Year: 2017, Page(s):306 - 314
Cited by:  Papers (8)
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In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H∞ View full abstract»

• ### Rate and Distortion Optimization for Reversible Data Hiding Using Multiple Histogram Shifting

Publication Year: 2017, Page(s):315 - 326
Cited by:  Papers (12)
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Histogram shifting (HS) embedding as a typical reversible data hiding scheme is widely investigated due to its high quality of stego-image. For HS-based embedding, the selected side information, i.e., peak and zero bins, usually greatly affects the rate and distortion performance of the stego-image. Due to the massive solution space and burden in distortion computation, conventional HS-based schem... View full abstract»

• ### Leader-Following Consensus of Nonlinear Multiagent Systems With Stochastic Sampling

Publication Year: 2017, Page(s):327 - 338
Cited by:  Papers (37)
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This paper is concerned with sampled-data leader-following consensus of a group of agents with nonlinear characteristic. A distributed consensus protocol with probabilistic sampling in two sampling periods is proposed. First, a general consensus criterion is derived for multiagent systems under a directed graph. A number of results in several special cases without transmittal delays or with the de... View full abstract»

• ### An Incremental Type-2 Meta-Cognitive Extreme Learning Machine

Publication Year: 2017, Page(s):339 - 353
Cited by:  Papers (12)
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Existing extreme learning algorithm have not taken into account four issues: 1) complexity; 2) uncertainty; 3) concept drift; and 4) high dimensionality. A novel incremental type-2 meta-cognitive extreme learning machine (ELM) called evolving type-2 ELM (eT2ELM) is proposed to cope with the four issues in this paper. The eT2ELM presents three main pillars of human meta-cognition: 1) what-to-learn;... View full abstract»

• ### Robust Object Tracking via Key Patch Sparse Representation

Publication Year: 2017, Page(s):354 - 364
Cited by:  Papers (46)
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Many conventional computer vision object tracking methods are sensitive to partial occlusion and background clutter. This is because the partial occlusion or little background information may exist in the bounding box, which tends to cause the drift. To this end, in this paper, we propose a robust tracker based on key patch sparse representation (KPSR) to reduce the disturbance of partial occlusio... View full abstract»

• ### $H_\infty$ Control for 2-D Fuzzy Systems With Interval Time-Varying Delays and Missing Measurements

Publication Year: 2017, Page(s):365 - 377
Cited by:  Papers (23)
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In this paper, we consider the H∞control problem for a class of 2-D Takagi-Sugeno fuzzy described by the second Fornasini-Machesini local state-space model with time delays and missing measurements. The state delays are allowed to be time-varying within a known interval. The measurement output is subject to randomly intermittent packet dropouts governed by a random sequence satisfying t... View full abstract»

• ### Superimposed Sparse Parameter Classifiers for Face Recognition

Publication Year: 2017, Page(s):378 - 390
Cited by:  Papers (13)
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In this paper, a novel classifier, called superimposed sparse parameter (SSP) classifier is proposed for face recognition. SSP is motivated by two phase test sample sparse representation (TPTSSR) and linear regression classification (LRC), which can be treated as the extended of sparse representation classification (SRC). SRC uses all the train samples to produce the sparse representation vector f... View full abstract»

• ### A Nonhomogeneous Cuckoo Search Algorithm Based on Quantum Mechanism for Real Parameter Optimization

Publication Year: 2017, Page(s):391 - 402
Cited by:  Papers (5)
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Cuckoo search (CS) algorithm is a nature-inspired search algorithm, in which all the individuals have identical search behaviors. However, this simple homogeneous search behavior is not always optimal to find the potential solution to a special problem, and it may trap the individuals into local regions leading to premature convergence. To overcome the drawback, this paper presents a new variant o... View full abstract»

• ### Adaptive Fuzzy Control Design for Stochastic Nonlinear Switched Systems With Arbitrary Switchings and Unmodeled Dynamics

Publication Year: 2017, Page(s):403 - 414
Cited by:  Papers (112)
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This paper deals with the problem of adaptive fuzzy output feedback control for a class of stochastic nonlinear switched systems. The controlled system in this paper possesses unmeasured states, completely unknown nonlinear system functions, unmodeled dynamics, and arbitrary switchings. A state observer which does not depend on the switching signal is constructed to tackle the unmeasured states. F... View full abstract»

• ### Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

Publication Year: 2017, Page(s):415 - 424
Cited by:  Papers (1)
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Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given ... View full abstract»

• ### Stochastic Optimal Regulation of Nonlinear Networked Control Systems by Using Event-Driven Adaptive Dynamic Programming

Publication Year: 2017, Page(s):425 - 438
Cited by:  Papers (5)
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In this paper, an event-driven stochastic adaptive dynamic programming (ADP)-based technique is introduced for nonlinear systems with a communication network within its feedback loop. A near optimal control policy is designed using an actor-critic framework and ADP with event sampled state vector. First, the system dynamics are approximated by using a novel neural network (NN) identifier with even... View full abstract»

• ### Latent Max-Margin Multitask Learning With Skelets for 3-D Action Recognition

Publication Year: 2017, Page(s):439 - 448
Cited by:  Papers (9)
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Recent emergence of low-cost and easy-operating depth cameras has reinvigorated the research in skeleton-based human action recognition. However, most existing approaches overlook the intrinsic interdependencies between skeleton joints and action classes, thus suffering from unsatisfactory recognition performance. In this paper, a novel latent max-margin multitask learning model is proposed for 3-... View full abstract»

• ### Cross-Modal Retrieval With CNN Visual Features: A New Baseline

Publication Year: 2017, Page(s):449 - 460
Cited by:  Papers (24)
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Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than o... View full abstract»

• ### A Benchmark Test Suite for Dynamic Evolutionary Multiobjective Optimization

Publication Year: 2017, Page(s):461 - 472
Cited by:  Papers (4)
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Growing trend of the dynamic multiobjective optimization research in the evolutionary computation community has increased the need for challenging and conceptually simple benchmark test suite to assess the optimization performance of an algorithm. This paper proposes a new dynamic multiobjective benchmark test suite which contains a number of component functions with clearly defined properties to ... View full abstract»

• ### A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems

Publication Year: 2017, Page(s):473 - 484
Cited by:  Papers (10)
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Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point ... View full abstract»

• ### Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning

Publication Year: 2017, Page(s):485 - 498
Cited by:  Papers (5)
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An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as ab... View full abstract»

• ### Learning Instance Correlation Functions for Multilabel Classification

Publication Year: 2017, Page(s):499 - 510
Cited by:  Papers (5)
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Multilabel learning has a wide range of potential applications in reality. It attracts a great deal of attention during the past years and has been extensively studied in many fields including image annotation and text categorization. Although many efforts have been made for multilabel learning, there are two challenging issues remaining, i.e., how to exploit the correlations and how to tackle the... View full abstract»

• ### An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks

Publication Year: 2017, Page(s):511 - 523
Cited by:  Papers (5)
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In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented b... View full abstract»

• ### Classifying a Person’s Degree of Accessibility From Natural Body Language During Social Human–Robot Interactions

Publication Year: 2017, Page(s):524 - 538
Cited by:  Papers (3)
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For social robots to be successfully integrated and accepted within society, they need to be able to interpret human social cues that are displayed through natural modes of communication. In particular, a key challenge in the design of social robots is developing the robot's ability to recognize a person's affective states (emotions, moods, and attitudes) in order to respond appropriately during s... View full abstract»

• ### A Two-Phase Multiobjective Evolutionary Algorithm for Enhancing the Robustness of Scale-Free Networks Against Multiple Malicious Attacks

Publication Year: 2017, Page(s):539 - 552
Cited by:  Papers (8)
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Designing robust networks has attracted increasing attentions in recent years. Most existing work focuses on improving the robustness of networks against a specific type of attacks. However, networks which are robust against one type of attacks may not be robust against another type of attacks. In the real-world situations, different types of attacks may happen simultaneously. Therefore, we use th... View full abstract»

## Aims & Scope

The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics.

Full Aims & Scope

## 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