# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 25 of 31
• ### Table of contents

Publication Year: 2015, Page(s):C1 - 1389
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• ### IEEE Transactions on Cybernetics publication information

Publication Year: 2015, Page(s): C2
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• ### Human-Like Behavior Generation Based on Head-Arms Model for Robot Tracking External Targets and Body Parts

Publication Year: 2015, Page(s):1390 - 1400
Cited by:  Papers (6)
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Facing and pointing toward moving targets is a usual and natural behavior in daily life. Social robots should be able to display such coordinated behaviors in order to interact naturally with people. For instance, a robot should be able to point and look at specific objects. This is why, a scheme to generate coordinated head-arm motion for a humanoid robot with two degrees-of-freedom for the head ... View full abstract»

• ### Nonrigid Structure From Motion via Sparse Representation

Publication Year: 2015, Page(s):1401 - 1413
Cited by:  Papers (17)
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This paper proposes a new approach for nonrigid structure from motion with occlusion, based on sparse representation. We address the occlusion problem based on the latest developments on sparse representation: matrix completion, which can recover the observation matrix that has high percentages of missing data and can also reduce the noises and outliers in the known elements. We introduce sparse t... View full abstract»

• ### Toward Generalization of Automated Temporal Abstraction to Partially Observable Reinforcement Learning

Publication Year: 2015, Page(s):1414 - 1425
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Temporal abstraction for reinforcement learning (RL) aims to decrease learning time by making use of repeated sub-policy patterns in the learning task. Automatic extraction of abstractions during RL process is difficult but has many challenges such as dealing with the curse of dimensionality. Various studies have explored the subject under the assumption that the problem domain is fully observable... View full abstract»

• ### A Variational Approach to Simultaneous Image Segmentation and Bias Correction

Publication Year: 2015, Page(s):1426 - 1437
Cited by:  Papers (20)
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This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is s... View full abstract»

• ### Improving Estimation of Distribution Algorithm on Multimodal Problems by Detecting Promising Areas

Publication Year: 2015, Page(s):1438 - 1449
Cited by:  Papers (10)
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In this paper, a novel multiple sub-models maintenance technique, named maintaining and processing sub-models (MAPS), is proposed. MAPS aims to enhance the ability of estimation of distribution algorithms (EDAs) on multimodal problems. The advantages of MAPS over the existing multiple sub-models based EDAs stem from the explicit detection of the promising areas, which can save many function evalua... View full abstract»

• ### Network-Based Robust $mathscr {H}_{2}/mathscr {H}_infty$ Control for Linear Systems With Two-Channel Random Packet Dropouts and Time Delays

Publication Year: 2015, Page(s):1450 - 1462
Cited by:  Papers (15)
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This paper focuses on the robust output feedback ℋ2/ℋ∞ control issue for a class of discrete-time networked control systems with uncertain parameters and external disturbance. Sensor-to-controller and controller-to-actuator packet dropouts and time delays are considered simultaneously. According to the stochastic characteristic of the packet dropouts and ... View full abstract»

• ### Data Partition Learning With Multiple Extreme Learning Machines

Publication Year: 2015, Page(s):1463 - 1475
Cited by:  Papers (8)
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As demonstrated earlier, the learning accuracy of the single-layer-feedforward-network (SLFN) is generally far lower than expected, which has been a major bottleneck for many applications. In fact, for some large real problems, it is accepted that after tremendous learning time (within finite epochs), the network output error of SLFN will stop or reduce increasingly slowly. This report offers an e... View full abstract»

• ### LDA-Based Unified Topic Modeling for Similar TV User Grouping and TV Program Recommendation

Publication Year: 2015, Page(s):1476 - 1490
Cited by:  Papers (3)
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Social TV is a social media service via TV and social networks through which TV users exchange their experiences about TV programs that they are viewing. For social TV service, two technical aspects are envisioned: grouping of similar TV users to create social TV communities and recommending TV programs based on group and personal interests for personalizing TV. In this paper, we propose a unified... View full abstract»

• ### Approximation and Parameterized Runtime Analysis of Evolutionary Algorithms for the Maximum Cut Problem

Publication Year: 2015, Page(s):1491 - 1498
Cited by:  Papers (3)
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The maximum cut (MAX-CUT) problem is to find a bipartition of the vertices in a given graph such that the number of edges with ends in different sets reaches the largest. Though, several experimental investigations have shown that evolutionary algorithms (EAs) are efficient for this NP-complete problem, there is little theoretical work about EAs on the problem. In this paper, we theoretically inve... View full abstract»

• ### Learning Multiscale Active Facial Patches for Expression Analysis

Publication Year: 2015, Page(s):1499 - 1510
Cited by:  Papers (12)
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In this paper, we present a new idea to analyze facial expression by exploring some common and specific information among different expressions. Inspired by the observation that only a few facial parts are active in expression disclosure (e.g., around mouth, eye), we try to discover the common and specific patches which are important to discriminate all the expressions and only a particular expres... View full abstract»

• ### Network-Based Output Tracking Control for a Class of T-S Fuzzy Systems That Can Not Be Stabilized by Nondelayed Output Feedback Controllers

Publication Year: 2015, Page(s):1511 - 1524
Cited by:  Papers (20)
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This paper investigates network-based output tracking control for a T-S fuzzy system that can not be stabilized by a nondelayed fuzzy static output feedback controller, but can be stabilized by a delayed fuzzy static output feedback controller. By intentionally introducing a communication network that produces proper network-induced delays in the feedback control loop, a stable and satisfactory tr... View full abstract»

• ### State Estimation of Discrete-Time Takagi–Sugeno Fuzzy Systems in a Network Environment

Publication Year: 2015, Page(s):1525 - 1536
Cited by:  Papers (58)
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In this paper, we investigate the H∞ filtering problem of discrete-time Takagi-Sugeno (T-S) fuzzy systems in a network environment. Different from the well used assumption that the normalized fuzzy weighting function for each subsystem is available at the filter node, we consider a practical case in which not only the measurement but also the premise variables are transmitted via... View full abstract»

• ### Popov-Type Criterion for Consensus in Nonlinearly Coupled Networks

Publication Year: 2015, Page(s):1537 - 1548
Cited by:  Papers (6)
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This paper addresses consensus problems in nonlinearly coupled networks of dynamic agents described by a common and arbitrary linear model. Interagent interaction rules are uncertain but satisfy the standard sector condition with known sector bounds; both the agent's model and interaction topology are time-invariant. A novel frequency-domain criterion for consensus is offered that is similar to an... View full abstract»

• ### Robust Match Fusion Using Optimization

Publication Year: 2015, Page(s):1549 - 1560
Cited by:  Papers (3)
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In this paper, we present a novel patch-based match and fusion algorithm by taking account of moving scene in a multiple exposure image sequence using optimization. A uniform iterative approach is developed to match and find the corresponding patches in different exposure images, which are then fused in each iteration. Our approach does not need to align the input multiple exposure images before t... View full abstract»

• ### Facilitating Image Search With a Scalable and Compact Semantic Mapping

Publication Year: 2015, Page(s):1561 - 1574
Cited by:  Papers (14)
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This paper introduces a novel approach to facilitating image search based on a compact semantic embedding. A novel method is developed to explicitly map concepts and image contents into a unified latent semantic space for the representation of semantic concept prototypes. Then, a linear embedding matrix is learned that maps images into the semantic space, such that each image is closer to its rele... View full abstract»

• ### Visual-Patch-Attention-Aware Saliency Detection

Publication Year: 2015, Page(s):1575 - 1586
Cited by:  Papers (16)
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The human visual system (HVS) can reliably perceive salient objects in an image, but, it remains a challenge to computationally model the process of detecting salient objects without prior knowledge of the image contents. This paper proposes a visual-attention-aware model to mimic the HVS for salient-object detection. The informative and directional patches can be seen as visual stimuli, and used ... View full abstract»

• ### Adaptive Neural Stabilizing Controller for a Class of Mismatched Uncertain Nonlinear Systems by State and Output Feedback

Publication Year: 2015, Page(s):1587 - 1596
Cited by:  Papers (11)
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In this paper, first, an adaptive neural network (NN) state-feedback controller for a class of nonlinear systems with mismatched uncertainties is proposed. By using a radial basis function NN (RBFNN), a bound of unknown nonlinear functions is approximated so that no information about the upper bound of mismatched uncertainties is required. Then, an observer-based adaptive controller based on RBFNN... View full abstract»

• ### An Integrated Approach to Global Synchronization and State Estimation for Nonlinear Singularly Perturbed Complex Networks

Publication Year: 2015, Page(s):1597 - 1609
Cited by:  Papers (12)
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This paper aims to establish a unified framework to handle both the exponential synchronization and state estimation problems for a class of nonlinear singularly perturbed complex networks (SPCNs). Each node in the SPCN comprises both “slow” and “fast” dynamics that reflects the singular perturbation behavior. General sector-like nonlinear function is employed to descri... View full abstract»

• ### Robust Design of Fuzzy Structured Controllers via a Moving Boundaries Process

Publication Year: 2015, Page(s):1610 - 1621
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In this paper, we consider the design of a fuzzy structured controller for systems that can be well described by uncertain T-S fuzzy models. Finding such a controller is known to be computationally intractable by the conventional techniques. Therefore, to solve this design problem easily and directly, we utilize a moving boundary process together with a robust stability test, for finding a solutio... View full abstract»

• ### Irregular Cellular Learning Automata

Publication Year: 2015, Page(s):1622 - 1632
Cited by:  Papers (3)
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Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integrat... View full abstract»

• ### Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm

Publication Year: 2015, Page(s):1633 - 1646
Cited by:  Papers (2)
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This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and na... View full abstract»

• ### How Much Control is Enough for Network Connectivity Preservation and Collision Avoidance?

Publication Year: 2015, Page(s):1647 - 1656
Cited by:  Papers (4)
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For a multiagent system in free space, the agents are required to generate sufficiently large cohesive force for network connectivity preservation and sufficiently large repulsive force for collision avoidance. This paper gives an energy function based approach for estimating the control force in a general setting. In particular, the force estimated for network connectivity preservation and collis... View full abstract»

• ### IT2 Fuzzy-Rough Sets and Max Relevance-Max Significance Criterion for Attribute Selection

Publication Year: 2015, Page(s):1657 - 1668
Cited by:  Papers (3)
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One of the important problems in pattern recognition, machine learning, and data mining is the dimensionality reduction by attribute or feature selection. In this regard, this paper presents a feature selection method, based on interval type-2 (IT2) fuzzy-rough sets, where the features are selected by maximizing both relevance and significance of the features. By introducing the concept of lower a... 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