By Topic

# 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 339
• ### A Time Variant Log-Linear Learning Approach to the SET K-COVER Problem in Wireless Sensor Networks

Publication Year: 2017, Page(s):1 - 10
| | PDF (1179 KB)

Toward the global optimality of the SET K-COVER problem in wireless sensor networks, we view each sensor node as a rational player and propose a time variant log-linear learning algorithm (TVLLA) that relies on local information only. By defining the local utility as the normalized area covered by one node alone, we formulate the problem as a spatial potential game. The resulting optimal Nash equi... View full abstract»

• ### Synchronization of Reaction-Diffusion Neural Networks With Dirichlet Boundary Conditions and Infinite Delays

Publication Year: 2017, Page(s):1 - 13
| | PDF (1099 KB)

This paper is concerned with synchronization for a class of reaction-diffusion neural networks with Dirichlet boundary conditions and infinite discrete time-varying delays. By utilizing theories of partial differential equations, Green's formula, inequality techniques, and the concept of comparison, algebraic criteria are presented to guarantee master-slave synchronization of the underlying reacti... View full abstract»

• ### An Adaptive Multiobjective Particle Swarm Optimization Based on Multiple Adaptive Methods

Publication Year: 2017, Page(s):1 - 14
| | PDF (3506 KB)

Multiobjective particle swarm optimization (MOPSO) algorithms have attracted much attention for their promising performance in solving multiobjective optimization problems (MOPs). In this paper, an adaptive MOPSO (AMOPSO) algorithm, based on a hybrid framework of the solution distribution entropy and population spacing (SP) information, is developed to improve the search performance in terms of co... View full abstract»

• ### Sampled-Data Fuzzy Control for Nonlinear Coupled Parabolic PDE-ODE Systems

Publication Year: 2017, Page(s):1 - 13
| | PDF (783 KB)

In this paper, a sampled-data fuzzy control problem is addressed for a class of nonlinear coupled systems, which are described by a parabolic partial differential equation (PDE) and an ordinary differential equation (ODE). Initially, the nonlinear coupled system is accurately represented by the Takagi-Sugeno (T-S) fuzzy coupled parabolic PDE-ODE model. Then, based on the T-S fuzzy model, a novel t... View full abstract»

• ### A Bio-Inspired Approach to Traffic Network Equilibrium Assignment Problem

Publication Year: 2017, Page(s):1 - 12
| | PDF (2329 KB)

Finding an equilibrium state of the traffic assignment plays a significant role in the design of transportation networks. We adapt the path finding mathematical model of slime mold Physarum polycephalum to solve the traffic equilibrium assignment problem. We make three contributions in this paper. First, we propose a generalized Physarum model to solve the shortest path problem in directed and asy... View full abstract»

• ### Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis With Co-Occurrence Data

Publication Year: 2017, Page(s):1 - 13
| | PDF (1429 KB)

Using online consumer reviews as electronic word of mouth to assist purchase-decision making has become increasingly popular. The Web provides an extensive source of consumer reviews, but one can hardly read all reviews to obtain a fair evaluation of a product or service. A text processing framework that can summarize reviews, would therefore be desirable. A subtask to be performed by such a frame... View full abstract»

• ### A Two-Phase Evolutionary Approach for Compressive Sensing Reconstruction

Publication Year: 2017, Page(s):1 - 13
| | PDF (1917 KB) |  Media

Sparse signal reconstruction can be regarded as a problem of locating the nonzero entries of the signal. In presence of measurement noise, conventional methods such as l₁ norm relaxation methods and greedy algorithms, have shown their weakness in finding the nonzero entries accurately. In order to reduce the impact of noise and better locate the nonzero entries, in this paper, we propose a ... View full abstract»

• ### Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data

Publication Year: 2017, Page(s):1 - 13
| | PDF (1563 KB)

Generating highly accurate predictions for missing quality-of-service (QoS) data is an important issue. Latent factor (LF)-based QoS-predictors have proven to be effective in dealing with it. However, they are based on first-order solvers that cannot well address their target problem that is inherently bilinear and nonconvex, thereby leaving a significant opportunity for accuracy improvement. This... View full abstract»

• ### Correlation Filter Learning Toward Peak Strength for Visual Tracking

Publication Year: 2017, Page(s):1 - 14
| | PDF (2902 KB)

This paper presents a novel visual tracking approach to correlation filter learning toward peak strength of correlation response. Previous methods leverage all features of the target and the immediate background to learn a correlation filter. Some features, however, may be distractive to tracking, like those from occlusion and local deformation, resulting in unstable tracking performance. This pap... View full abstract»

• ### Learning Sparse Representation for Objective Image Retargeting Quality Assessment

Publication Year: 2017, Page(s):1 - 14
| | PDF (1959 KB)

The goal of image retargeting is to adapt source images to target displays with different sizes and aspect ratios. Different retargeting operators create different retargeted images, and a key problem is to evaluate the performance of each retargeting operator. Subjective evaluation is most reliable, but it is cumbersome and labor-consuming, and more importantly, it is hard to be embedded into onl... View full abstract»

• ### Finite-Time Synchronization of Coupled Hierarchical Hybrid Neural Networks With Time-Varying Delays

Publication Year: 2017, Page(s):1 - 10
| | PDF (667 KB)

This paper is concerned with the finite-time synchronization problem of coupled hierarchical hybrid delayed neural networks. This coupled hierarchical hybrid neural networks consist of a higher level switching and a lower level Markovian jumping. The time-varying delays are dependent on not only switching signal but also jumping mode. By using a less conservative weighted integral inequality and s... View full abstract»

• ### Adaptive Fuzzy Control for Nonstrict Feedback Systems With Unmodeled Dynamics and Fuzzy Dead Zone via Output Feedback

Publication Year: 2017, Page(s):1 - 13
| | PDF (4757 KB)

This paper investigates the problem of observer-based adaptive fuzzy control for a category of nonstrict feedback systems subject to both unmodeled dynamics and fuzzy dead zone. Through constructing a fuzzy state observer and introducing a center of gravity method, unmeasurable states are estimated and the fuzzy dead zone is defuzzified, respectively. By employing fuzzy logic systems to identify t... View full abstract»

• ### Neuronal State Estimation for Neural Networks With Two Additive Time-Varying Delay Components

Publication Year: 2017, Page(s):1 - 11
| | PDF (887 KB)

This paper is concerned with the state estimation for neural networks with two additive time-varying delay components. Three cases of these two time-varying delays are fully considered: 1) both delays are differentiable uniformly bounded with delay-derivative bounded by some constants; 2) one delay is continuous uniformly bounded while the other is differentiable uniformly bounded with delay-deriv... View full abstract»

• ### Aperiodic Optimal Linear Estimation for Networked Systems With Communication Uncertainties

Publication Year: 2017, Page(s):1 - 10
| | PDF (1494 KB)

The aperiodic optimal linear estimator design problem is investigated in this paper for networked systems with communication uncertainties, including delays and data losses, where the sampling and estimation are nonuniform and asynchronous. Based on the idea of measurement fusion, two approaches are proposed to design the aperiodic estimators, and it is shown that the estimator is equivalent to th... View full abstract»

• ### Networked Predictive Control for Nonlinear Systems With Arbitrary Region Quantizers

Publication Year: 2017, Page(s):1 - 12
| | PDF (1294 KB)

In this paper, networked predictive control is investigated for planar nonlinear systems with quantization by an extended state observer (ESO). The ESO is used not only to deal with nonlinear terms but also to generate predictive states for dealing with network-induced delays. Two arbitrary region quantizers are applied to take effective values of signals in forward channel and feedback channel, r... View full abstract»

• ### Multilayer Optimization of Heterogeneous Networks Using Grammatical Genetic Programming

Publication Year: 2017, Page(s):1 - 13
| | PDF (2718 KB)

Heterogeneous cellular networks are composed of macro cells (MCs) and small cells (SCs) in which all cells occupy the same bandwidth. Provision has been made under the third generation partnership project-long term evolution framework for enhanced intercell interference coordination (eICIC) between cell tiers. Expanding on previous works, this paper instruments grammatical genetic programming to e... View full abstract»

• ### Fast Variable Structure Stochastic Automaton for Discovering and Tracking Spatiotemporal Event Patterns

Publication Year: 2017, Page(s):1 - 14
| | PDF (1527 KB)

Discovering and tracking spatiotemporal event patterns have many applications. For example, in a smart-home project, a set of spatiotemporal pattern learning automata are used to monitor a user's repetitive activities, by which the home's automaticity can be promoted while some of his/her burdens can be reduced. Existing algorithms for spatiotemporal event pattern recognition in dynamic noisy envi... View full abstract»

• ### FaRoC: Fast and Robust Supervised Canonical Correlation Analysis for Multimodal Omics Data

Publication Year: 2017, Page(s):1 - 13
| | PDF (1085 KB)

One of the main problems associated with high dimensional multimodal real life data sets is how to extract relevant and significant features. In this regard, a fast and robust feature extraction algorithm, termed as FaRoC, is proposed, integrating judiciously the merits of canonical correlation analysis (CCA) and rough sets. The proposed method extracts new features sequentially from two multidime... View full abstract»

• ### Effects of Preview on Human Control Behavior in Tracking Tasks With Various Controlled Elements

Publication Year: 2017, Page(s):1 - 11
| | PDF (2159 KB)

This paper investigates how humans use a previewed target trajectory for control in tracking tasks with various controlled element dynamics. The human's hypothesized "near" and "far" control mechanisms are first analyzed offline in simulations with a quasi-linear model. Second, human control behavior is quantified by fitting the same model to measurements from a human-in-the-loop experiment, where... View full abstract»

• ### Analysis and Design of Synchronization for Heterogeneous Network

Publication Year: 2017, Page(s):1 - 10
| | PDF (1120 KB)

In this paper, we investigate the synchronization for heterogeneous network subject to event-triggering communication. The designed controller for each node includes reference generator (RG) and regulator. The predicted value of relative information between intermittent communication can significantly reduce the transmitted information. Based on the event triggering strategy and time-dependent thr... View full abstract»

• ### Cooperative Hierarchical PSO With Two Stage Variable Interaction Reconstruction for Large Scale Optimization

Publication Year: 2017, Page(s):1 - 15
| | PDF (2828 KB)

Large scale optimization problems arise in diverse fields. Decomposing the large scale problem into small scale subproblems regarding the variable interactions and optimizing them cooperatively are critical steps in an optimization algorithm. To explore the variable interactions and perform the problem decomposition tasks, we develop a two stage variable interaction reconstruction algorithm. A lea... View full abstract»

• ### Finite-Horizon H∞ Consensus Control of Time-Varying Multiagent Systems With Stochastic Communication Protocol

Publication Year: 2017, Page(s):1 - 11
| | PDF (751 KB)

This paper is concerned with the distributed H∞ consensus control problem for a discrete time-varying multiagent system with the stochastic communication protocol (SCP). A directed graph is used to characterize the communication topology of the multiagent network. The data transmission between each agent and the neighboring ones is implemented via a constrained communication channel where o... View full abstract»

• ### Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems

Publication Year: 2017, Page(s):1 - 12
| | PDF (2778 KB)

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practic... View full abstract»

• ### Distributed Consensus Optimization in Multiagent Networks With Time-Varying Directed Topologies and Quantized Communication

Publication Year: 2017, Page(s):1 - 14
| | PDF (616 KB)

This paper considers solving a class of optimization problems which are modeled as the sum of all agents' convex cost functions and each agent is only accessible to its individual function. Communication between agents in multiagent networks is assumed to be limited: each agent can only interact information with its neighbors by using time-varying communication channels with limited capacities. A ... View full abstract»

• ### Semantically Enhanced Online Configuration of Feedback Control Schemes

Publication Year: 2017, Page(s):1 - 14
| | PDF (1736 KB)

Recent progress toward the realization of the Internet of Things' has improved the ability of physical and soft/cyber entities to operate effectively within large-scale, heterogeneous systems. It is important that such capacity be accompanied by feedback control capabilities sufficient to ensure that the overall systems behave according to their specifications and meet their functional objective... 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