# IEEE Transactions on Cybernetics

### Early Access Articles

Early Access articles are made available in advance of the final electronic or print versions. Early Access articles are peer reviewed but may not be fully edited. They are fully citable from the moment they appear in IEEE Xplore.

## Filter Results

Displaying Results 1 - 25 of 365
• ### Abdominal-Waving Control of Tethered Bumblebees Based on Sarsa With Transformed Reward

Publication Year: 2018, Page(s):1 - 10
| | PDF (1836 KB)

Cyborg insects have attracted great attention as the flight performance they have is incomparable by micro aerial vehicles and play a critical role in supporting extensive applications. Approaches to construct cyborg insects consist of two major issues: 1) the stimulating paradigm and 2) the control policy. At present, most cyborg insects are constructed based on invasive methods, requiring the im... View full abstract»

• ### Multiview Clustering Based on Non-Negative Matrix Factorization and Pairwise Measurements

Publication Year: 2018, Page(s):1 - 14
| | PDF (2661 KB)

As we all know, multiview clustering has become a hot topic in machine learning and pattern recognition. Non-negative matrix factorization (NMF) has been one popular tool in multiview clustering due to its competitiveness and interpretation. However, the existing multiview clustering methods based on NMF only consider the similarity of intra-view, while neglecting the similarity of inter-view. In ... View full abstract»

• ### Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering

Publication Year: 2018, Page(s):1 - 15
| | PDF (2351 KB)

Collaborative filtering (CF) algorithms have been widely used to build recommender systems since they have distinguishing capability of sharing collective wisdoms and experiences. However, they may easily fall into the trap of the Matthew effect, which tends to recommend popular items and hence less popular items become increasingly less popular. Under this circumstance, most of the items in the r... View full abstract»

• ### Lifelong Metric Learning

Publication Year: 2018, Page(s):1 - 12
| | PDF (2115 KB)

The state-of-the-art online learning approaches are only capable of learning the metric for predefined tasks. In this paper, we consider a lifelong learning problem to mimic human learning,' i.e., endowing a new capability to the learned metric for a new task from new online samples and incorporating the previous experiences. Therefore, we propose a new metric learning framework: lifelong metric... View full abstract»

• ### Improving Speech Related Facial Action Unit Recognition by Audiovisual Information Fusion

Publication Year: 2018, Page(s):1 - 14
| | PDF (2142 KB)

It is challenging to recognize facial action unit (AU) from spontaneous facial displays, especially when they are accompanied by speech. The major reason is that the information is extracted from a single source, i.e., the visual channel, in the current practice. However, facial activity is highly correlated with voice in natural human communications. Instead of solely improving visual observation... View full abstract»

• ### Fuzzy-Model-Based Sliding Mode Control of Nonlinear Descriptor Systems

Publication Year: 2018, Page(s):1 - 11
| | PDF (1026 KB)

This paper addresses the problem of sliding mode control (SMC) for a type of uncertain time-delay nonlinear descriptor systems represented by T-S fuzzy models. One crucial contributing factor is to put forward a novel integral fuzzy switching manifold involved with time delay. Compared with previous results, the key benefit of the new manifold is that the input matrices via different subsystems ar... View full abstract»

• ### Pinning Controllers for Activation Output Tracking of Boolean Network Under One-Bit Perturbation

Publication Year: 2018, Page(s):1 - 11
| | PDF (764 KB)

This paper studies pinning controllers for activation output tracking (AOT) of Boolean network under one-bit perturbation, based on the semitensor product of matrices. First, the definition of AOT with respect to an activation number is presented, where the activation number means the number of active outputs whose logical variables are 1 s. Then, several criteria are established for AOT issue. Fu... View full abstract»

• ### Quantized Feedback Control of Fuzzy Markov Jump Systems

Publication Year: 2018, Page(s):1 - 10
| | PDF (732 KB)

This paper addresses the problem of quantized feedback control of nonlinear Markov jump systems (MJSs). The nonlinear plant is represented by a class of fuzzy MJSs with time-varying delay based on a Takagi-Sugeno fuzzy model. The quantized signal is utilized for control purpose and the sector bound approach is exploited to deal with quantization errors. By constructing a Lyapunov function which de... View full abstract»

• ### A Consistency and Consensus-Based Goal Programming Method for Group Decision-Making With Interval-Valued Intuitionistic Multiplicative Preference Relations

Publication Year: 2018, Page(s):1 - 15
| | PDF (672 KB)

Interval-valued intuitionistic multiplicative preference relations (IVIMPRs) form a suitable conceptual framework to represent and process simultaneously uncertain preferred and nonpreferred judgments of decision makers (DMs). The focus of this paper is on group decision-making (GDM) problems realized with IVIMPRs. First, a consistency index is introduced to evaluate the consistency degree for int... View full abstract»

• ### A Knowledge-Based Semisupervised Hierarchical Online Topic Detection Framework

Publication Year: 2018, Page(s):1 - 15
| | PDF (3368 KB) |  Media

Topic models have achieved big success in recent years. To detect topics in a text stream, various online topic models have been proposed in the literature. The limitations of these works include that: 1) most of them run with fixed topic numbers and 2) the overlaps between the topics may enlarge in the evolving process. Hierarchical topic model is a candidate solution to these problems since it c... View full abstract»

• ### Multidirectional Prediction Approach for Dynamic Multiobjective Optimization Problems

Publication Year: 2018, Page(s):1 - 13
| | PDF (3859 KB) |  Media

Various real-world multiobjective optimization problems are dynamic, requiring evolutionary algorithms (EAs) to be able to rapidly track the moving Pareto front of an optimization problem once an environmental change occurs. To this end, several methods have been developed to predict the new location of the moving Pareto set (PS) so that the population can be reinitialized around the predicted loc... View full abstract»

• ### Sparse Multiview Task-Centralized Ensemble Learning for ASD Diagnosis Based on Age- and Sex-Related Functional Connectivity Patterns

Publication Year: 2018, Page(s):1 - 14
| | PDF (2597 KB)

Autism spectrum disorder (ASD) is an age- and sex-related neurodevelopmental disorder that alters the brain's functional connectivity (FC). The changes caused by ASD are associated with different age- and sex-related patterns in neuroimaging data. However, most contemporary computer-assisted ASD diagnosis methods ignore the aforementioned age-/sex-related patterns. In this paper, we propose a nove... View full abstract»

• ### Leader-Follower Consensus of Multiagent Systems With Time Delays Over Finite Fields

Publication Year: 2018, Page(s):1 - 6
| | PDF (382 KB)

This paper studies the leader-follower consensus of multiagent systems with time delays and switching topology over finite fields. First, an equivalent algebraic form is established for leader-follower multiagent systems with time delays over finite fields. Second, based on the algebraic form, a necessary and sufficient condition is presented for the finite-field leader-follower consensus with tim... View full abstract»

• ### Constrained Multiobjective Nonlinear Optimization: A User Preference Enabling Method

Publication Year: 2018, Page(s):1 - 13
| | PDF (2258 KB) |  Media

A novel user preference enabling (UPE) method is developed to solve general constrained nonlinear multiple objective optimization (MOO) problems. User wish lists on the preferred range of each objective function are introduced and incorporated into the MOO formulation to form a user-preferred (UP) MOO problem. A theoretical foundation of the UP feasible region of MOO problems is developed. The dev... View full abstract»

• ### Learning Neural Representations for Network Anomaly Detection

Publication Year: 2018, Page(s):1 - 14
| | PDF (2617 KB) |  Media

This paper proposes latent representation models for improving network anomaly detection. Well-known anomaly detection algorithms often suffer from challenges posed by network data, such as high dimension and sparsity, and a lack of anomaly data for training, model selection, and hyperparameter tuning. Our approach is to introduce new regularizers to a classical autoencoder (AE) and a variational ... View full abstract»

• ### Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI

Publication Year: 2018, Page(s):1 - 11
| | PDF (4137 KB)

Common spatial pattern (CSP)-based spatial filtering has been most popularly applied to electroencephalogram (EEG) feature extraction for motor imagery (MI) classification in brain-computer interface (BCI) application. The effectiveness of CSP is highly affected by the frequency band and time window of EEG segments. Although numerous algorithms have been designed to optimize the spectral bands of ... View full abstract»

• ### A Complex Varying-Parameter Convergent-Differential Neural-Network for Solving Online Time-Varying Complex Sylvester Equation

Publication Year: 2018, Page(s):1 - 13
| | PDF (3172 KB)

A novel recurrent neural network, which is named as complex varying-parameter convergent-differential neural network (CVP-CDNN), is proposed in this paper for solving the time-varying complex Sylvester equation. Two kinds of CVP-CDNNs (i.e., CVP-CDNN Type I and Type II) are illustrated and proved to be effective. The proposed CVP-CDNNs can achieve super-exponential performance if the linear activa... View full abstract»

• ### A Discrete Multiobjective Particle Swarm Optimizer for Automated Assembly of Parallel Cognitive Diagnosis Tests

Publication Year: 2018, Page(s):1 - 14
| | PDF (1843 KB)

Parallel test assembly has long been an important yet challenging topic in educational assessment. Cognitive diagnosis models (CDMs) are a new class of assessment models and have drawn increasing attention for being able to measure examinees' ability in detail. However, few studies have been devoted to the parallel test assembly problem in CDMs (CDM-PTA). To fill the gap, this paper models CDM-PTA... View full abstract»

• ### Dynamic Boundary Fuzzy Control Design of Semilinear Parabolic PDE Systems With Spatially Noncollocated Discrete Observation

Publication Year: 2018, Page(s):1 - 11
| | PDF (807 KB)

The problem of dynamic boundary fuzzy control design is investigated in this paper for nonlinear parabolic partial differential equation (PDE) systems with spatially noncollocated discrete observation. Two cases of noncollocated discrete observation in space (i.e., pointwise observation in space and local piecewise uniform observation in space) are considered, respectively. The spatially noncolloc... View full abstract»

• ### Synchronization Analysis of Two-Time-Scale Nonlinear Complex Networks With Time-Scale-Dependent Coupling

Publication Year: 2018, Page(s):1 - 13
| | PDF (3760 KB)

In this paper, a time-scale-dependent coupling scheme for two-time-scale nonlinear complex networks is proposed. According to this scheme, the inner coupling matrices are related to the fast dynamics of individual subsystems, but are no longer time-scale-independent. Designing time-scale-dependent inner coupling matrices is motivated by the fact that the difference of time scales is an essential f... View full abstract»

• ### Synchronization of Multiple Reaction-Diffusion Neural Networks With Heterogeneous and Unbounded Time-Varying Delays

Publication Year: 2018, Page(s):1 - 12
| | PDF (1517 KB)

The synchronization problem of multiple/coupled reaction-diffusion neural networks with time-varying delays is investigated. Differing from the existing considerations, state delays among distinct neurons and coupling delays among different subnetworks are included in the proposed model, the assumptions posed on the arisen delays are very weak, time-varying, heterogeneous, even unbounded delays ar... View full abstract»

• ### Framework of Randomized Distribution Features for Visual Representation and Categorization

Publication Year: 2018, Page(s):1 - 8
| | PDF (797 KB)

This paper introduces a framework to deal with the distribution of descriptive features, which preserves the advantages of the vectorial representation and computational efficiency of histogram-based techniques, and inherits the rigorous theoretical guarantee and competitive performance of metric-based ones. The methods developed under this framework describe the underlying distribution of a set o... View full abstract»

• ### Distributed Impulsive Quasi-Synchronization of Lur'e Networks With Proportional Delay

Publication Year: 2018, Page(s):1 - 11
| | PDF (687 KB)

This paper investigates the exponential synchronization of nonidentically coupled Lur'e dynamical networks with proportional delay. Since the heterogeneities existed in different Lur'e systems, quasi-synchronization rather than complete synchronization is thus discussed. Different from general time delay, the proportional delay is a type of unbounded time-varying delay, which tremendously increase... View full abstract»

• ### Admissibility Analysis for Interval Type-2 Fuzzy Descriptor Systems Based on Sliding Mode Control

Publication Year: 2018, Page(s):1 - 9
| | PDF (1304 KB)

This paper is concerned with the sliding mode control of nonlinear singular systems in terms of the interval type-2 (IT2) fuzzy model. To better approximate the nonlinear systems, the modeling errors are considered in the IT2 fuzzy model. The uncertainties in membership functions are expressed based on their boundedness. Admissibility conditions are obtained via a linear matrix inequalities approa... View full abstract»

• ### Energy-to-Peak State Estimation for Static Neural Networks With Interval Time-Varying Delays

Publication Year: 2018, Page(s):1 - 13
| | PDF (1084 KB)

This paper is concerned with energy-to-peak state estimation on static neural networks (SNNs) with interval time-varying delays. The objective is to design suitable delay-dependent state estimators such that the peak value of the estimation error state can be minimized for all disturbances with bounded energy. Note that the Lyapunov-Krasovskii functional (LKF) method plus proper integral inequalit... 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