IEEE Transactions on Cybernetics

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Publication Year: 2016, Page(s):C1 - 1
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• IEEE Transactions on Cybernetics publication information

Publication Year: 2016, Page(s): C2
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• A Study on Estimation of Joint Force Through Isometric Index Finger Abduction With the Help of SEMG Peaks for Biomedical Applications

Publication Year: 2016, Page(s):2 - 8
Cited by:  Papers (5)
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We propose a new method to estimate joint force using a biomechanical muscle model and peaks of surface electromyography (SEMG). The SEMG measurement was carried out from the first dorsal interosseous muscle during isometric index finger abduction. The SEMG peaks were used as the input of the biomechanical muscle model which is a transfer function to generate the force. The force estimation perfor... View full abstract»

• Neural Controller Design-Based Adaptive Control for Nonlinear MIMO Systems With Unknown Hysteresis Inputs

Publication Year: 2016, Page(s):9 - 19
Cited by:  Papers (88)
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This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form. The studied systems are composed of ${N}$ subsystems in pure feedback structure and the interconnection terms are contained in every equation of each subsystem. Moreover, the studied systems consider the effects of Prandtl-Ishlinskii (PI) hysteresis model. It is for the first ... View full abstract»

• Fast Sound Source Localization Using Two-Level Search Space Clustering

Publication Year: 2016, Page(s):20 - 26
Cited by:  Papers (13)
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Steered response power phase transform (SRP-PHAT) is a method that is widely used for robust sound source localization (SSL). However, since SRP-PHAT searches over a large number of candidate locations, it is too slow to run in real-time for large-scale microphone array systems. In this paper, we propose a robust two-level search space clustering method to speed-up SRP-PHAT-based SSL. The proposed... View full abstract»

• Spectral Multimodal Hashing and Its Application to Multimedia Retrieval

Publication Year: 2016, Page(s):27 - 38
Cited by:  Papers (12)
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In recent years, multimedia retrieval has sparked much research interest in the multimedia, pattern recognition, and data mining communities. Although some attempts have been made along this direction, performing fast multimodal search at very large scale still remains a major challenge in the area. While hashing-based methods have recently achieved promising successes in speeding-up large-scale s... View full abstract»

• No-Reference Image Blur Assessment Based on Discrete Orthogonal Moments

Publication Year: 2016, Page(s):39 - 50
Cited by:  Papers (86)
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Blur is a key determinant in the perception of image quality. Generally, blur causes spread of edges, which leads to shape changes in images. Discrete orthogonal moments have been widely studied as effective shape descriptors. Intuitively, blur can be represented using discrete moments since noticeable blur affects the magnitudes of moments of an image. With this consideration, this paper presents... View full abstract»

• Robust Visual Tracking via Exclusive Context Modeling

Publication Year: 2016, Page(s):51 - 63
Cited by:  Papers (30)
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In this paper, we formulate particle filter-based object tracking as an exclusive sparse learning problem that exploits contextual information. To achieve this goal, we propose the context-aware exclusive sparse tracker (CEST) to model particle appearances as linear combinations of dictionary templates that are updated dynamically. Learning the representation of each particle is formulated as an e... View full abstract»

• Ensemble and Arithmetic Recombination-Based Speciation Differential Evolution for Multimodal Optimization

Publication Year: 2016, Page(s):64 - 74
Cited by:  Papers (27)
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Multimodal optimization problems consists of multiple equal or comparable spatially distributed solutions. Niching and clustering differential evolution (DE) techniques have been demonstrated to be highly effective for solving such problems. The key challenge in the speciation niching technique is to balance between local solution exploitation and global exploration. Our proposal enhances explorat... View full abstract»

• Consensus Control With Failure—Wait or Abandon?

Publication Year: 2016, Page(s):75 - 84
Cited by:  Papers (6)
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This paper introduces and solves a decision-making problem under the context of consensus control with failure. We study an optimal consensus control problem in which n autonomous agents try to arrive at a target at the same time. One of the agents suddenly fails and the rest n - 1 agents can either wait or abandon the failed agent. If they wait, they must slow down and delay the consensus time. I... View full abstract»

• Adaptive Neural Control of a Class of Output-Constrained Nonaffine Systems

Publication Year: 2016, Page(s):85 - 95
Cited by:  Papers (48)
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In this paper, we present a novel tracking controller for a class of uncertain nonaffine systems with time-varying asymmetric output constraints. Firstly, the original nonaffine constrained (in the sense of the output signal) control system is transformed into a output-feedback control problem of an unconstrained affine system in normal form. As a result, stabilization of the transformed system is... View full abstract»

• Multiobjective Optimization of Linear Cooperative Spectrum Sensing: Pareto Solutions and Refinement

Publication Year: 2016, Page(s):96 - 108
Cited by:  Papers (6)
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In linear cooperative spectrum sensing, the weights of secondary users and detection threshold should be optimally chosen to minimize missed detection probability and to maximize secondary network throughput. Since these two objectives are not completely compatible, we study this problem from the viewpoint of multiple-objective optimization. We aim to obtain a set of evenly distributed Pareto solu... View full abstract»

• Evidential Matrix Metrics as Distances Between Meta-Data Dependent Bodies of Evidence

Publication Year: 2016, Page(s):109 - 122
Cited by:  Papers (2)
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As part of the theory of belief functions, we address the problem of appraising the similarity between bodies of evidence in a relevant way using metrics. Such metrics are called evidential distances and must be computed from mathematical objects depicting the information inside bodies of evidence. Specialization matrices are such objects and, therefore, an evidential distance can be obtained by c... View full abstract»

• Pervasive Sound Sensing: A Weakly Supervised Training Approach

Publication Year: 2016, Page(s):123 - 135
Cited by:  Papers (4)
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Modern smartphones present an ideal device for pervasive sensing of human behavior. Microphones have the potential to reveal key information about a person's behavior. However, they have been utilized to a significantly lesser extent than other smartphone sensors in the context of human behavior sensing. We postulate that, in order for microphones to be useful in behavior sensing applications, the... View full abstract»

• A Gesture Recognition System for Detecting Behavioral Patterns of ADHD

Publication Year: 2016, Page(s):136 - 147
Cited by:  Papers (6)
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We present an application of gesture recognition using an extension of dynamic time warping (DTW) to recognize behavioral patterns of attention deficit hyperactivity disorder (ADHD). We propose an extension of DTW using one-class classifiers in order to be able to encode the variability of a gesture category, and thus, perform an alignment between a gesture sample and a gesture class. We model the... View full abstract»

• Consensus of Linear Multi-Agent Systems by Distributed Event-Triggered Strategy

Publication Year: 2016, Page(s):148 - 157
Cited by:  Papers (150)
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This paper studies the consensus problem of multi-agent systems with general linear dynamics. We propose a novel event-triggered control scheme with some desirable features, namely, distributed, asynchronous, and independent. It is shown that consensus of the controlled multi-agent system can be reached asymptotically. The feasibility of the event-triggered strategy is further verified by the excl... View full abstract»

• Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach

Publication Year: 2016, Page(s):158 - 170
Cited by:  Papers (71)
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Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a populatio... View full abstract»

• FLS-Based Adaptive Synchronization Control of Complex Dynamical Networks With Nonlinear Couplings and State-Dependent Uncertainties

Publication Year: 2016, Page(s):171 - 180
Cited by:  Papers (55)
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This paper is concerned with the problem of synchronization control of complex dynamical networks (CDN) subject to nonlinear couplings and uncertainties. An fuzzy logical system-based adaptive distributed controller is designed to achieve the synchronization. The asymptotic convergence of synchronization errors is analyzed by combining algebraic graph theory and Lyapunov theory. In contrast to the... View full abstract»

• Cluster Prototypes and Fuzzy Memberships Jointly Leveraged Cross-Domain Maximum Entropy Clustering

Publication Year: 2016, Page(s):181 - 193
Cited by:  Papers (4)
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The classical maximum entropy clustering (MEC) algorithm usually cannot achieve satisfactory results in the situations where the data is insufficient, incomplete, or distorted. To address this problem, inspired by transfer learning, the specific cluster prototypes and fuzzy memberships jointly leveraged (CPM-JL) framework for cross-domain MEC (CDMEC) is firstly devised in this paper, and then the ... View full abstract»

• Robust Extreme Learning Machine With its Application to Indoor Positioning

Publication Year: 2016, Page(s):194 - 205
Cited by:  Papers (30)
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The increasing demands of location-based services have spurred the rapid development of indoor positioning system and indoor localization system interchangeably (IPSs). However, the performance of IPSs suffers from noisy measurements. In this paper, two kinds of robust extreme learning machines (RELMs), corresponding to the close-to-mean constraint, and the small-residual constraint, have been pro... View full abstract»

• Learning Flexible Graph-Based Semi-Supervised Embedding

Publication Year: 2016, Page(s):206 - 218
Cited by:  Papers (17)
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This paper introduces a graph-based semi-supervised embedding method as well as its kernelized version for generic classification and recognition tasks. The aim is to combine the merits of flexible manifold embedding and nonlinear graph-based embedding for semi-supervised learning. The proposed linear method will be flexible since it estimates a nonlinear manifold that is the closest one to a line... View full abstract»

• Self-Adaptive Differential Evolution Algorithm With Zoning Evolution of Control Parameters and Adaptive Mutation Strategies

Publication Year: 2016, Page(s):219 - 232
Cited by:  Papers (40)
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The performance of the differential evolution (DE) algorithm is significantly affected by the choice of mutation strategies and control parameters. Maintaining the search capability of various control parameter combinations throughout the entire evolution process is also a key issue. A self-adaptive DE algorithm with zoning evolution of control parameters and adaptive mutation strategies is propos... View full abstract»

• Semi-Supervised Nonnegative Matrix Factorization via Constraint Propagation

Publication Year: 2016, Page(s):233 - 244
Cited by:  Papers (25)
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As is well known, nonnegative matrix factorization (NMF) is a popular nonnegative dimensionality reduction method which has been widely used in computer vision, document clustering, and image analysis. However, traditional NMF is an unsupervised learning mode which cannot fully utilize the priori or supervised information. To this end, semi-supervised NMF methods have been proposed by incorporatin... View full abstract»

• MOD* Lite: An Incremental Path Planning Algorithm Taking Care of Multiple Objectives

Publication Year: 2016, Page(s):245 - 257
Cited by:  Papers (10)
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The need for determining a path from an initial location to a target one is a crucial task in many applications, such as virtual simulations, robotics, and computer games. Almost all of the existing algorithms are designed to find optimal or suboptimal solutions considering only a single objective, namely path length. However, in many real life application path length is not the sole criteria for ... View full abstract»

• Weakly Supervised Human Fixations Prediction

Publication Year: 2016, Page(s):258 - 269
Cited by:  Papers (14)
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Automatically predicting human eye fixations is a useful technique that can facilitate many multimedia applications, e.g., image retrieval, action recognition, and photo retargeting. Conventional approaches are frustrated by two drawbacks. First, psychophysical experiments show that an object-level interpretation of scenes influences eye movements significantly. Most of the existing saliency model... View full abstract»

Aims & Scope

The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics.

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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