# IEEE Transactions on Cybernetics

## Volume 48 Issue 2 • Feb. 2018

The purchase and pricing options for this item are unavailable. Select items are only available as part of a subscription package. You may try again later or contact us for more information.

## Filter Results

Displaying Results 1 - 25 of 34

Publication Year: 2018, Page(s):C1 - 449
| PDF (170 KB)
• ### IEEE Transactions on Cybernetics

Publication Year: 2018, Page(s): C2
| PDF (62 KB)
• ### Data-Driven Adaptive Probabilistic Robust Optimization Using Information Granulation

Publication Year: 2018, Page(s):450 - 462
| | PDF (817 KB) | HTML

In this paper, we consider a generic class of adaptive optimization problems under uncertainty, and develop a data-driven paradigm of adaptive probabilistic robust optimization (APRO) in a robust and computationally tractable manner. The paradigm comprises two phases: 1) bilayer information granulation (IG), which involves the data-mining techniques and nested decomposition of convex sets that est... View full abstract»

• ### Designing Hyperchaotic Cat Maps With Any Desired Number of Positive Lyapunov Exponents

Publication Year: 2018, Page(s):463 - 473
Cited by:  Papers (1)
| | PDF (1542 KB) | HTML

Generating chaotic maps with expected dynamics of users is a challenging topic. Utilizing the inherent relation between the Lyapunov exponents (LEs) of the Cat map and its associated Cat matrix, this paper proposes a simple but efficient method to construct an n-dimensional (n-D) hyperchaotic Cat map (HCM) with any desired number of positive LEs. The method first generates two basic n-D Cat matric... View full abstract»

• ### moGrams: A Network-Based Methodology for Visualizing the Set of Nondominated Solutions in Multiobjective Optimization

Publication Year: 2018, Page(s):474 - 485
| | PDF (845 KB) | HTML

An appropriate visualization of multiobjective nondominated solutions is a valuable asset for decision making. Although there are methods for visualizing the solutions in the design space, they do not provide any information about their relationship. In this paper, we propose a novel methodology that allows the visualization of the nondominated solutions in the design space and their relationships... View full abstract»

• ### WoCE: A framework for Clustering Ensemble by Exploiting the Wisdom of Crowds Theory

Publication Year: 2018, Page(s):486 - 499
| | PDF (1225 KB) | HTML

The wisdom of crowds (WOCs), as a theory in the social science, gets a new paradigm in computer science. The WOC theory explains that the aggregate decision made by a group is often better than those of its individual members if specific conditions are satisfied. This paper presents a novel framework for unsupervised and semisupervised cluster ensemble by exploiting the WOC theory. We employ four ... View full abstract»

• ### Policy Iteration for $H_infty$ Optimal Control of Polynomial Nonlinear Systems via Sum of Squares Programming

Publication Year: 2018, Page(s):500 - 509
| | PDF (892 KB) | HTML

Sum of squares (SOS) polynomials have provided a computationally tractable way to deal with inequality constraints appearing in many control problems. It can also act as an approximator in the framework of adaptive dynamic programming. In this paper, an approximate solution to the H∞ optimal control of polynomial nonlinear systems is proposed. Under a given attenuation coefficien... View full abstract»

• ### Virtual Network Embedding via Monte Carlo Tree Search

Publication Year: 2018, Page(s):510 - 521
Cited by:  Papers (1)
| | PDF (836 KB) | HTML

Network virtualization helps overcome shortcomings of the current Internet architecture. The virtualized network architecture enables coexistence of multiple virtual networks (VNs) on an existing physical infrastructure. VN embedding (VNE) problem, which deals with the embedding of VN components onto a physical network, is known to be NP-hard. In this paper, we propose two VNE algorithms: MaVEn-M ... View full abstract»

• ### Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems

Publication Year: 2018, Page(s):522 - 531
| | PDF (2206 KB) | HTML

This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different fro... View full abstract»

• ### Robust Estimation of ARX Models With Time Varying Time Delays Using Variational Bayesian Approach

Publication Year: 2018, Page(s):532 - 542
| | PDF (1275 KB) | HTML

This paper is concerned with robust identification of processes with time-varying time delays. In reality, the delay values do not simply change randomly, but there is a correlation between consecutive delays. In this paper, the correlation of time delay is modeled by the transition probability of a Markov chain. Furthermore, the measured data are often contaminated by outliers, and therefore, t-d... View full abstract»

• ### The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems

Publication Year: 2018, Page(s):543 - 555
| | PDF (2290 KB) | HTML

We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each sub... View full abstract»

• ### A Scan-Line Forest Growing-Based Hand Segmentation Framework With Multipriority Vertex Stereo Matching for Wearable Devices

Publication Year: 2018, Page(s):556 - 570
| | PDF (1971 KB) | HTML

A hand segmentation framework is proposed for 3-D hand gesture interaction for wearable devices. In this framework, all the objects in a scene are regarded as directed trees in a forest, and the problem of the hand segmentation can be converted into finding the target tree (called hand tree) in the forest with proper hand properties including color consistency, space consistency, disparity, and ha... View full abstract»

• ### Adaptive Trajectory Tracking of Nonholonomic Mobile Robots Using Vision-Based Position and Velocity Estimation

Publication Year: 2018, Page(s):571 - 582
| | PDF (1543 KB) | HTML

Despite tremendous efforts made for years, trajectory tracking control (TC) of a nonholonomic mobile robot (NMR) without global positioning system remains an open problem. The major reason is the difficulty to localize the robot by using its onboard sensors only. In this paper, a newly designed adaptive trajectory TC method is proposed for the NMR without its position, orientation, and velocity me... View full abstract»

• ### Exact and Approximate Stability of Solutions to Traveling Salesman Problems

Publication Year: 2018, Page(s):583 - 595
| | PDF (572 KB) | HTML

This paper presents the stability analysis of an optimal tour for the symmetric traveling salesman problem (TSP) by obtaining stability regions. The stability region of an optimal tour is the set of all cost changes for which that solution remains optimal and can be understood as the margin of optimality for a solution with respect to perturbations in the problem data. It is known that it is not p... View full abstract»

• ### Pareto-Optimal Model Selection via SPRINT-Race

Publication Year: 2018, Page(s):596 - 610
| | PDF (1355 KB) | HTML

In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of Pareto-optimal models that optimize by compromising more than one predefined objectives simultaneously. This paper introduces SPRINT-Race, the first multi-objective racing algorithm in a fixed-confidence setting, which is based on the sequential probability ratio with indiffere... View full abstract»

• ### On the Exploration of Information From the DTW Cost Matrix for Online Signature Verification

Publication Year: 2018, Page(s):611 - 624
| | PDF (1872 KB) | HTML

This paper explores the utility of information derived from the dynamic time warping (DTW) cost matrix for the problem of online signature verification. The prior works in literature primarily utilize only the DTW scores to authenticate a test signature. To the best of our knowledge, the characteristics of the warping path (used for the alignment) in the cost matrix is hardly exploited for verific... View full abstract»

• ### A Novel Switching-Based Control Framework for Improved Task Performance in Teleoperation System With Asymmetric Time-Varying Delays

Publication Year: 2018, Page(s):625 - 638
| | PDF (2200 KB)

This paper addresses the adaptive control for task-space teleoperation systems with constrained predefined synchronization error, where a novel switched control framework is investigated. Based on multiple Lyapunov-Krasovskii functionals method, the stability of the resulting closed-loop system is established in the sense of state-independent input-to-output stability. Compared with previous work,... View full abstract»

• ### An Intelligent Actuator Fault Reconstruction Scheme for Robotic Manipulators

Publication Year: 2018, Page(s):639 - 647
| | PDF (2715 KB) | HTML

This paper investigates a difficult problem of reconstructing actuator faults for robotic manipulators. An intelligent approach with fast reconstruction property is developed. This is achieved by using observer technique. This scheme is capable of precisely reconstructing the actual actuator fault. It is shown by Lyapunov stability analysis that the reconstruction error can converge to zero after ... View full abstract»

• ### An Adaptive Semisupervised Feature Analysis for Video Semantic Recognition

Publication Year: 2018, Page(s):648 - 660
| | PDF (1696 KB) | HTML

Video semantic recognition usually suffers from the curse of dimensionality and the absence of enough high-quality labeled instances, thus semisupervised feature selection gains increasing attentions for its efficiency and comprehensibility. Most of the previous methods assume that videos with close distance (neighbors) have similar labels and characterize the intrinsic local structure through a p... View full abstract»

• ### A Novel Variable Precision Reduction Approach to Comprehensive Knowledge Systems

Publication Year: 2018, Page(s):661 - 674
| | PDF (1430 KB) | HTML Media

A comprehensive knowledge system reveals the intangible insights hidden in an information system by integrating information from multiple data sources in a synthetical manner. In this paper, we present a variable precision reduction theory, underpinned by two new concepts: 1) distribution tables and 2) genealogical binary trees. Sufficient and necessary conditions to extract comprehensive knowledg... View full abstract»

• ### Asynchronous Periodic Edge-Event Triggered Control for Double-Integrator Networks With Communication Time Delays

Publication Year: 2018, Page(s):675 - 688
| | PDF (882 KB) | HTML

This paper focuses on the average consensus of double-integrator networked systems based on the asynchronous periodic edge-event triggered control. The asynchronous property lies in the edge event-detecting procedure. For different edges, their event detections are performed at different times and the corresponding events occur independently of each other. When an event is activated, the two adjac... View full abstract»

• ### Progressive Semisupervised Learning of Multiple Classifiers

Publication Year: 2018, Page(s):689 - 702
| | PDF (1656 KB) | HTML

Semisupervised learning methods are often adopted to handle datasets with very small number of labeled samples. However, conventional semisupervised ensemble learning approaches have two limitations: 1) most of them cannot obtain satisfactory results on high dimensional datasets with limited labels and 2) they usually do not consider how to use an optimization process to enlarge the training set. ... View full abstract»

• ### Discovering the Relationship Between Generalization and Uncertainty by Incorporating Complexity of Classification

Publication Year: 2018, Page(s):703 - 715
| | PDF (1042 KB) | HTML

The generalization ability of a classifier learned from a training set is usually dependent on the classifier's uncertainty, which is often described by the fuzziness of the classifier's outputs on the training set. Since the exact dependency relation between generalization and uncertainty of a classifier is quite complicated, it is difficult to clearly or explicitly express this relation in gener... View full abstract»

• ### Expanding Training Data for Facial Image Super-Resolution

Publication Year: 2018, Page(s):716 - 729
| | PDF (7656 KB) | HTML Media

The quality of training data is very important for learning-based facial image super-resolution (SR). The more similarity between training data and testing input is, the better SR results we can have. To generate a better training set of low/high resolution training facial images for a particular testing input, this paper is the first work that proposes expanding the training data for improving fa... View full abstract»

• ### Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance

Publication Year: 2018, Page(s):730 - 741
| | PDF (1424 KB) | HTML

This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for we... 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