# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 25 of 25

Publication Year: 2017, Page(s):C1 - 1121
| PDF (166 KB)
• ### IEEE Transactions on Cybernetics

Publication Year: 2017, Page(s): C2
| PDF (65 KB)
• ### Incremental Passivity and Incremental Passivity-Based Output Regulation for Switched Discrete-Time Systems

Publication Year: 2017, Page(s):1122 - 1132
Cited by:  Papers (6)
| | PDF (576 KB) | HTML

This paper investigates incremental passivity and output regulation for switched discrete-time systems. We develop the results in two parts. First of all, a concept of incremental passivity is proposed to describe the overall incremental passivity property of a switched discrete-time system in the absence of the classic incremental passivity property of the subsystems. A condition for incremental ... View full abstract»

• ### Coalition Formation and Spectrum Sharing of Cooperative Spectrum Sensing Participants

Publication Year: 2017, Page(s):1133 - 1146
Cited by:  Papers (4)
| | PDF (1242 KB) | HTML

In cognitive radio networks, self-interested secondary users (SUs) desire to maximize their own throughput. They compete with each other for transmit time once the absence of primary users (PUs) is detected. To satisfy the requirement of PU protection, on the other hand, they have to form some coalitions and cooperate to conduct spectrum sensing. Such dilemma of SUs between competition and coopera... View full abstract»

• ### An Optimal Divisioning Technique to Stabilization Synthesis of T–S Fuzzy Delayed Systems

Publication Year: 2017, Page(s):1147 - 1156
Cited by:  Papers (19)
| | PDF (769 KB) | HTML

This paper investigates the problem of stability analysis and stabilization for Takagi-Sugeno (T-S) fuzzy systems with time-varying delay. By using appropriately chosen Lyapunov-Krasovskii functional, together with the reciprocally convex a new sufficient stability condition with the idea of delay partitioning approach is proposed for the delayed T-S fuzzy systems, which significantly reduces cons... View full abstract»

• ### GrCS: Granular Computing-Based Crowd Segmentation

Publication Year: 2017, Page(s):1157 - 1168
Cited by:  Papers (5)
| | PDF (3132 KB) | HTML

Crowd segmentation is important in serving as the basis for a wide range of crowd analysis tasks such as density estimation and behavior understanding. However, due to interocclusions, perspective distortion, clutter background, and random crowd distribution, localizing crowd segments is technically a very challenging task. This paper proposes a novel crowd segmentation framework-based on granular... View full abstract»

• ### Efficient Markov Blanket Discovery and Its Application

Publication Year: 2017, Page(s):1169 - 1179
Cited by:  Papers (4)
| | PDF (888 KB) | HTML

In a Bayesian network (BN), a target node is independent of all other nodes given its Markov blanket (MB), and finding the MB has many applications, including feature selection and BN structure learning. We propose a new MB discovery algorithm, simultaneous MB (STMB), to improve the efficiency of the existing topology-based MB discovery algorithms. The proposed method removes the necessity of enfo... View full abstract»

• ### Bi-Level Semantic Representation Analysis for Multimedia Event Detection

Publication Year: 2017, Page(s):1180 - 1197
Cited by:  Papers (110)
| | PDF (3279 KB) | HTML

Multimedia event detection has been one of the major endeavors in video event analysis. A variety of approaches have been proposed recently to tackle this problem. Among others, using semantic representation has been accredited for its promising performance and desirable ability for human-understandable reasoning. To generate semantic representation, we usually utilize several external image/video... View full abstract»

• ### Empirical Sensitivity Analysis of Discretization Parameters for Fault Pattern Extraction From Multivariate Time Series Data

Publication Year: 2017, Page(s):1198 - 1209
Cited by:  Papers (4)
| | PDF (2122 KB) | HTML

It has been a challenge to find patterns in a time series of sensor data for fault detection in a system. Since it is usually not straightforward to discover meaningful features and rules directly from complex time series, data discretization has been popularly employed to reduce data size while preserving meaningful features from the original data, for which the choice of appropriate discretizati... View full abstract»

• ### Finite-Time Control for Robust Tracking Consensus in MASs With an Uncertain Leader

Publication Year: 2017, Page(s):1210 - 1223
Cited by:  Papers (12)
| | PDF (3721 KB) | HTML

This paper investigates the finite-time control for robust tracking consensus problems of multiagent systems with an uncertain leader for situations where the state of the considered active leader may not be measured and the directed network topology is time-varying. Based on the neighbor-based state-estimation rule and a new Lyapunov stability analysis method, a continuous and nonlinear distribut... View full abstract»

• ### Discrete-Time Deterministic $Q$ -Learning: A Novel Convergence Analysis

Publication Year: 2017, Page(s):1224 - 1237
Cited by:  Papers (37)
| | PDF (1616 KB) | HTML

In this paper, a novel discrete-time deterministic Q-learning algorithm is developed. In each iteration of the developed Q-learning algorithm, the iterative Q function is updated for all the state and control spaces, instead of updating for a single state and a single control in traditional Q-learning algorithm. A new convergence criterion is established to guarantee that the iterative Q function ... View full abstract»

• ### Multiagent Reinforcement Learning With Sparse Interactions by Negotiation and Knowledge Transfer

Publication Year: 2017, Page(s):1238 - 1250
Cited by:  Papers (2)
| | PDF (1607 KB) | HTML

Reinforcement learning has significant applications for multiagent systems, especially in unknown dynamic environments. However, most multiagent reinforcement learning (MARL) algorithms suffer from such problems as exponential computation complexity in the joint state-action space, which makes it difficult to scale up to realistic multiagent problems. In this paper, a novel algorithm named negotia... View full abstract»

• ### Switched Tracking Control of the Lower Limb During Asynchronous Neuromuscular Electrical Stimulation: Theory and Experiments

Publication Year: 2017, Page(s):1251 - 1262
Cited by:  Papers (4)
| | PDF (1581 KB) | HTML

Neuromuscular electrical stimulation (NMES) induces muscle contractions via electrical stimuli. NMES can be used for rehabilitation and to enable functional movements; however, a fundamental limitation is the early onset of fatigue. Asynchronous stimulation is a method that can reduce fatigue by utilizing multiple stimulation channels to segregate and switch between different sets of recruited mot... View full abstract»

• ### Combating Curse of Dimensionality in Resilient Monitoring Systems: Conditions for Lossless Decomposition

Publication Year: 2017, Page(s):1263 - 1272
Cited by:  Papers (1)
| | PDF (439 KB) | HTML

Resilient monitoring systems (RMSs) are sensor networks that degrade gracefully under cyber-attacks on their sensors. The recently developed RMSs, while being effective in the attacked sensors identification and isolation, exhibited a drawback in their operation-an exponentially increasing assessment time as a function of the number of sensors in the network. To combat this curse of dimensionality... View full abstract»

• ### Distributed Secure Coordinated Control for Multiagent Systems Under Strategic Attacks

Publication Year: 2017, Page(s):1273 - 1284
Cited by:  Papers (18)
| | PDF (1096 KB) | HTML

This paper studies a distributed secure consensus tracking control problem for multiagent systems subject to strategic cyber attacks modeled by a random Markov process. A hybrid stochastic secure control framework is established for designing a distributed secure control law such that mean-square exponential consensus tracking is achieved. A connectivity restoration mechanism is considered and the... View full abstract»

• ### Multimodal Image Registration With Line Segments by Selective Search

Publication Year: 2017, Page(s):1285 - 1298
Cited by:  Papers (7)
| | PDF (1568 KB) | HTML

This paper proposes a line segment-based image registration method. Edges are detected from images by a modified Canny operator, and line segments are then extracted from these edges. At registration, triplets (quaternions) of line segment correspondences are tentatively formed by applying the distance and orientation constraints, which determine an intermediate transformation. Those triplets (qua... View full abstract»

• ### A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion

Publication Year: 2017, Page(s):1299 - 1312
| | PDF (1640 KB) | HTML Media

Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equi... View full abstract»

• ### Instance Annotation via Optimal BoW for Weakly Supervised Object Localization

Publication Year: 2017, Page(s):1313 - 1324
Cited by:  Papers (3)
| | PDF (1736 KB) | HTML

In this paper, we aim at irregular-shape object localization under weak supervision. With over-segmentation, this task can be transformed into multiple-instance context. However, most multiple-instance learning methods only emphasize single most positive instance in a positive bag to optimize bag-level classification, and leads to imprecise or incomplete localization. To address this issue, we pro... View full abstract»

• ### The Designated Convergence Rate Problems of Consensus or Flocking of Double-Integrator Agents With General Nonequal Velocity and Position Couplings: Further Results and Patterns of Convergence Rate Contours

Publication Year: 2017, Page(s):1325 - 1335
Cited by:  Papers (2)
| | PDF (481 KB) | HTML

This paper considers the designated convergence rate (DCR) (or the designated convergence margin) problems of consensus or flocking of coupled double-integrator agents. The DCR problems are more valuable for systems design than just convergence or stability conditions. The system setting in this paper is general, i.e., the velocity coupling and position coupling (VCPC) between agents, respectively... View full abstract»

• ### FUIQA: Fetal Ultrasound Image Quality Assessment With Deep Convolutional Networks

Publication Year: 2017, Page(s):1336 - 1349
Cited by:  Papers (11)
| | PDF (2746 KB) | HTML

The quality of ultrasound (US) images for the obstetric examination is crucial for accurate biometric measurement. However, manual quality control is a labor intensive process and often impractical in a clinical setting. To improve the efficiency of examination and alleviate the measurement error caused by improper US scanning operation and slice selection, a computerized fetal US image quality as... View full abstract»

• ### Introducing IEEE Collabratec

Publication Year: 2017, Page(s): 1350
| PDF (2159 KB)
• ### Member Get-A-Member (MGM) Program

Publication Year: 2017, Page(s): 1351
| PDF (3462 KB)
• ### Together, we are advancing technology

Publication Year: 2017, Page(s): 1352
| PDF (537 KB)
• ### IEEE Transactions on Cybernetics

Publication Year: 2017, Page(s): C3
| PDF (233 KB)
• ### IEEE Transactions on Cybernetics

Publication Year: 2017, Page(s): C4
| PDF (117 KB)

## 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