# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 25 of 28

Publication Year: 2017, Page(s):C1 - 553
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• ### IEEE Transactions on Cybernetics

Publication Year: 2017, Page(s): C2
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• ### An Approximate Approach to Automatic Kernel Selection

Publication Year: 2017, Page(s):554 - 565
Cited by:  Papers (1)
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Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational vir... View full abstract»

• ### Perceptually Guided Photo Retargeting

Publication Year: 2017, Page(s):566 - 578
Cited by:  Papers (6)
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We propose perceptually guided photo retargeting, which shrinks a photo by simulating a human's process of sequentially perceiving visually/semantically important regions in a photo. In particular, we first project the local features (graphlets in this paper) onto a semantic space, wherein visual cues such as global spatial layout and rough geometric context are exploited. Thereafter, a sparsity-c... View full abstract»

• ### Fuzzy Adaptive Tracking Control of Constrained Nonlinear Switched Stochastic Pure-Feedback Systems

Publication Year: 2017, Page(s):579 - 588
Cited by:  Papers (28)
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In this paper, the fuzzy adaptive control problem for a class of switched stochastic nonlinear systems in pure feedback form with output constraint is addressed. By proposing a nonlinear mapping, the constrained system is transformed into an unconstrained one, with equivalent control objective. All signals in the closed-loop system are proved to be semiglobally uniformly ultimately bounded. Meanwh... View full abstract»

• ### Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network

Publication Year: 2017, Page(s):589 - 599
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Relational model learning is useful for numerous practical applications. Many algorithms have been proposed in recent years to tackle this important yet challenging problem. Existing algorithms utilize only binary directional link data to recover hidden network structures. However, there exists far richer and more meaningful information in other parts of a network which one can (and should) exploi... View full abstract»

• ### Weighted Joint Sparse Representation for Removing Mixed Noise in Image

Publication Year: 2017, Page(s):600 - 611
Cited by:  Papers (29)
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Joint sparse representation (JSR) has shown great potential in various image processing and computer vision tasks. Nevertheless, the conventional JSR is fragile to outliers. In this paper, we propose a weighted JSR (WJSR) model to simultaneously encode a set of data samples that are drawn from the same subspace but corrupted with noise and outliers. Our model is desirable to exploit the common inf... View full abstract»

• ### An Overview and Empirical Comparison of Distance Metric Learning Methods

Publication Year: 2017, Page(s):612 - 625
Cited by:  Papers (5)
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In this paper, we first offer an overview of advances in the field of distance metric learning. Then, we empirically compare selected methods using a common experimental protocol. The number of distance metric learning algorithms proposed keeps growing due to their effectiveness and wide application. However, existing surveys are either outdated or they focus only on a few methods. As a result, th... View full abstract»

• ### Symmetrical Hierarchical Stochastic Searching on the Line in Informative and Deceptive Environments

Publication Year: 2017, Page(s):626 - 635
Cited by:  Papers (5)
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A stochastic point location (SPL) problem aims to find a target parameter on a 1-D line by operating a controlled random walk and receiving information from a stochastic environment (SE). If the target parameter changes randomly, we call the parameter dynamic; otherwise static. SE can be 1) informative (p &gt; 0.5 where p represents the probability for an environment providing a correct sugges... View full abstract»

• ### Multimodal Estimation of Distribution Algorithms

Publication Year: 2017, Page(s):636 - 650
Cited by:  Papers (15)
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Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) a... View full abstract»

• ### Blind Domain Adaptation With Augmented Extreme Learning Machine Features

Publication Year: 2017, Page(s):651 - 660
Cited by:  Papers (6)
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In practical applications, the test data often have different distribution from the training data leading to suboptimal visual classification performance. Domain adaptation (DA) addresses this problem by designing classifiers that are robust to mismatched distributions. Existing DA algorithms use the unlabeled test data from target domain during training time in addition to the source domain data.... View full abstract»

• ### Improved Stability Condition for Takagi–Sugeno Fuzzy Systems With Time-Varying Delay

Publication Year: 2017, Page(s):661 - 670
Cited by:  Papers (26)
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In this paper, the stability analysis problem of Takagi-Sugeno fuzzy systems with time-varying delay is investigated. By utilizing the Wirtinger-based integral inequality and the improved reciprocally convex combination technique, an improved stability condition is derived in terms of linear matrix inequalities. A numerical example is given to demonstrate the efficiency of the obtained result. View full abstract»

• ### Robust Filtering for a Class of Networked Nonlinear Systems With Switching Communication Channels

Publication Year: 2017, Page(s):671 - 682
Cited by:  Papers (13)
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This paper is concerned with the problem of robust filter design for a class of discrete-time networked nonlinear systems. The Takagi-Sugeno fuzzy model is employed to represent the underlying nonlinear dynamics. A multi-channel communication scheme that involves a channel switching phenomenon described by a Markov chain is proposed for data transmission. Two typical communication imperfections, n... View full abstract»

• ### An Event-Triggered ADP Control Approach for Continuous-Time System With Unknown Internal States

Publication Year: 2017, Page(s):683 - 694
Cited by:  Papers (40)
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This paper proposes a novel event-triggered adaptive dynamic programming (ADP) control method for nonlinear continuous-time system with unknown internal states. Comparing with the traditional ADP design with a fixed sample period, the event-triggered method samples the state and updates the controller only when it is necessary. Therefore, the computation cost and transmission load are reduced. Usu... View full abstract»

• ### Template Deformation-Based 3-D Reconstruction of Full Human Body Scans From Low-Cost Depth Cameras

Publication Year: 2017, Page(s):695 - 708
Cited by:  Papers (6)
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Full human body shape scans provide valuable data for a variety of applications including anthropometric surveying, clothing design, human-factors engineering, health, and entertainment. However, the high price, large volume, and difficulty of operating professional 3-D scanners preclude their use in home entertainment. Recently, portable low-cost red green blue-depth cameras such as the Kinect ha... View full abstract»

• ### Cooperative Semi-Global Output Regulation of Nonlinear Strict-Feedback Multi-Agent Systems With Nonidentical Relative Degrees

Publication Year: 2017, Page(s):709 - 719
Cited by:  Papers (1)
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In this paper, we study the cooperative semi-global output regulation problem for a class of nonlinear strict-feedback multi-agent systems, where the subsystems are assumed to have nonidentical relative degrees. We first introduce the so-called distributed internal model that converts our problem into the cooperative semi-global stabilization problem of the corresponding augmented system composed ... View full abstract»

• ### Game Design and Analysis for Price-Based Demand Response: An Aggregate Game Approach

Publication Year: 2017, Page(s):720 - 730
Cited by:  Papers (27)
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In this paper, an aggregate game is adopted for the modeling and analysis of energy consumption control in smart grid. Since the electricity users' cost functions depend on the aggregate energy consumption, which is unknown to the end users, an average consensus protocol is employed to estimate it. By neighboring communication among the users about their estimations on the aggregate energy consump... View full abstract»

• ### Highly Efficient Framework for Predicting Interactions Between Proteins

Publication Year: 2017, Page(s):731 - 743
Cited by:  Papers (12)
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Protein-protein interactions (PPIs) play a central role in many biological processes. Although a large amount of human PPI data has been generated by high-throughput experimental techniques, they are very limited compared to the estimated 130 000 protein interactions in humans. Hence, automatic methods for human PPI-detection are highly desired. This work proposes a novel framework, i.e., Low-rank... View full abstract»

• ### Task Sensitive Feature Exploration and Learning for Multitask Graph Classification

Publication Year: 2017, Page(s):744 - 758
Cited by:  Papers (10)
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Multitask learning (MTL) is commonly used for jointly optimizing multiple learning tasks. To date, all existing MTL methods have been designed for tasks with feature-vector represented instances, but cannot be applied to structure data, such as graphs. More importantly, when carrying out MTL, existing methods mainly focus on exploring overall commonality or disparity between tasks for learning, bu... View full abstract»

• ### Sliced Inverse Regression With Adaptive Spectral Sparsity for Dimension Reduction

Publication Year: 2017, Page(s):759 - 771
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Dimension reduction is an important topic in pattern analysis and machine learning, and it has wide applications in feature representation and pattern classification. In the past two decades, sliced inverse regression (SIR) has attracted much research efforts due to its effectiveness and efficacy in dimension reduction. However, two drawbacks limit further applications of SIR. First, the computati... View full abstract»

• ### Distributed $k$ -Means Algorithm and Fuzzy $c$ -Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory

Publication Year: 2017, Page(s):772 - 783
Cited by:  Papers (35)
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This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To ob... View full abstract»

• ### Hierarchical Relaxed Partitioning System for Activity Recognition

Publication Year: 2017, Page(s):784 - 795
Cited by:  Papers (4)
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A hierarchical relaxed partitioning system (HRPS) is proposed for recognizing similar activities which has a feature space with multiple overlaps. Two feature descriptors are built from the human motion analysis of a 2-D stick figure to represent cyclic and noncyclic activities. The HRPS first discerns the pure and impure activities, i.e., with no overlaps and multiple overlaps in the feature spac... View full abstract»

• ### Largest Matching Areas for Illumination and Occlusion Robust Face Recognition

Publication Year: 2017, Page(s):796 - 808
Cited by:  Papers (4)
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In this paper, we introduce a novel approach to face recognition which simultaneously tackles three combined challenges: (1) uneven illumination; (2) partial occlusion; and (3) limited training data. The new approach performs lighting normalization, occlusion de-emphasis and finally face recognition, based on finding the largest matching area (LMA) at each point on the face, as opposed to traditio... View full abstract»

• ### An Inertial Projection Neural Network for Solving Variational Inequalities

Publication Year: 2017, Page(s):809 - 814
Cited by:  Papers (32)
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Recently, projection neural network (PNN) was proposed for solving monotone variational inequalities (VIs) and related convex optimization problems. In this paper, considering the inertial term into first order PNNs, an inertial PNN (IPNN) is also proposed for solving VIs. Under certain conditions, the IPNN is proved to be stable, and can be applied to solve a broader class of constrained optimiza... View full abstract»

• ### Introducing IEEE Collabratec

Publication Year: 2017, Page(s): 815
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## 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