# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 24 of 24

Publication Year: 2015, Page(s): C1
| PDF (383 KB)
• ### IEEE Transactions on Cybernetics publication information

Publication Year: 2015, Page(s): C2
| PDF (135 KB)
• ### 3-D Model-Based Tracking for UAV Indoor Localization

Publication Year: 2015, Page(s):869 - 879
Cited by:  Papers (18)
| | PDF (1724 KB) | HTML

This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We a... View full abstract»

• ### Universal Fuzzy Models and Universal Fuzzy Controllers for Discrete-Time Nonlinear Systems

Publication Year: 2015, Page(s):880 - 887
Cited by:  Papers (5)
| | PDF (491 KB) | HTML

This paper investigates the problems of universal fuzzy model and universal fuzzy controller for discrete-time nonaffine nonlinear systems (NNSs). It is shown that a kind of generalized T-S fuzzy model is the universal fuzzy model for discrete-time NNSs satisfying a sufficient condition. The results on universal fuzzy controllers are presented for two classes of discrete-time stabilizable NNSs. Co... View full abstract»

• ### Adaptive Distributed Outlier Detection for WSNs

Publication Year: 2015, Page(s):902 - 913
Cited by:  Papers (18)
| | PDF (1847 KB) | HTML

The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecti... View full abstract»

• ### Feature Selection in Supervised Saliency Prediction

Publication Year: 2015, Page(s):914 - 926
Cited by:  Papers (9)
| | PDF (2382 KB) | HTML

There is an increasing interest in learning mappings from features to saliency maps based on human fixation data on natural images. These models have achieved better results than most bottom-up (unsupervised) saliency models. However, they usually use a large set of features trying to account for all possible saliency-related factors, which increases time cost and leaves the truly effective featur... View full abstract»

• ### Graph-Based Segmentation for RGB-D Data Using 3-D Geometry Enhanced Superpixels

Publication Year: 2015, Page(s):927 - 940
Cited by:  Papers (13)
| | PDF (2304 KB) | HTML

With the advances of depth sensing technologies, color image plus depth information (referred to as RGB-D data hereafter) is more and more popular for comprehensive description of 3-D scenes. This paper proposes a two-stage segmentation method for RGB-D data: 1) oversegmentation by 3-D geometry enhanced superpixels and 2) graph-based merging with label cost from superpixels. In the oversegmentatio... View full abstract»

• ### Parameter Selection of Gaussian Kernel for One-Class SVM

Publication Year: 2015, Page(s):941 - 953
Cited by:  Papers (14)
| | PDF (2695 KB) | HTML

One-class classification (OCC) builds models using only the samples from one class (the target class) so as to predict whether a new-coming sample belongs to the target class or not. OCC widely exists in many application fields, such as fault detection. As an effective tool for OCC, one-class SVM (OCSVM) with the Gaussian kernel has received much attention recently. However, its kernel parameter s... View full abstract»

• ### Graph Ensemble Boosting for Imbalanced Noisy Graph Stream Classification

Publication Year: 2015, Page(s):954 - 968
Cited by:  Papers (20)
| | PDF (2365 KB) | HTML

Many applications involve stream data with structural dependency, graph representations, and continuously increasing volumes. For these applications, it is very common that their class distributions are imbalanced with minority (or positive) samples being only a small portion of the population, which imposes significant challenges for learning models to accurately identify minority samples. This p... View full abstract»

• ### Reliability Modeling and Life Estimation Using an Expectation Maximization Based Wiener Degradation Model for Momentum Wheels

Publication Year: 2015, Page(s):969 - 977
Cited by:  Papers (2)
| | PDF (836 KB) | HTML

The momentum wheel (MW) plays a significant role in ensuring the success of satellite missions, the reliability information of MW can be provided by collecting degradation data when there exists certain performance characteristics that degrade over time. In this paper, we develop a reliability modeling and life estimation approach for MW used in satellites based on the expectation maximization (EM... View full abstract»

• ### Model Learning and Knowledge Sharing for a Multiagent System With Dyna-Q Learning

Publication Year: 2015, Page(s):978 - 990
Cited by:  Papers (6)
| | PDF (2283 KB) | HTML

In a multiagent system, if agents' experiences could be accessible and assessed between peers for environmental modeling, they can alleviate the burden of exploration for unvisited states or unseen situations so as to accelerate the learning process. Since how to build up an effective and accurate model within a limited time is an important issue, especially for complex environments, this paper in... View full abstract»

• ### A Video, Text, and Speech-Driven Realistic 3-D Virtual Head for Human–Machine Interface

Publication Year: 2015, Page(s):991 - 1002
Cited by:  Papers (5)
| | PDF (1849 KB) | HTML

A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facia... View full abstract»

• ### Multilayer Obstacle-Avoiding X-Architecture Steiner Minimal Tree Construction Based on Particle Swarm Optimization

Publication Year: 2015, Page(s):1003 - 1016
Cited by:  Papers (2)
| | PDF (1649 KB) | HTML

As the basic model for very large scale integration routing, the Steiner minimal tree (SMT) can be used in various practical problems, such as wire length optimization, congestion, and time delay estimation. In this paper, an effective algorithm based on particle swarm optimization is presented to construct a multilayer obstacle-avoiding X-architecture SMT (ML-OAXSMT). First, a pretreatment strate... View full abstract»

• ### Reinforcement Learning for Port-Hamiltonian Systems

Publication Year: 2015, Page(s):1017 - 1027
Cited by:  Papers (10)
| | PDF (956 KB) | HTML

Passivity-based control (PBC) for port-Hamiltonian systems provides an intuitive way of achieving stabilization by rendering a system passive with respect to a desired storage function. However, in most instances the control law is obtained without any performance considerations and it has to be calculated by solving a complex partial differential equation (PDE). In order to address these issues w... View full abstract»

• ### Clause States Based Configuration Checking in Local Search for Satisfiability

Publication Year: 2015, Page(s):1028 - 1041
| | PDF (1620 KB) | HTML

Two-mode stochastic local search (SLS) and focused random walk (FRW) are the two most influential paradigms of SLS algorithms for the propositional satisfiability (SAT) problem. Recently, an interesting idea called configuration checking (CC) was proposed to handle the cycling problem in SLS. The CC idea has been successfully used to improve SLS algorithms for SAT, resulting in state-of-the-art so... View full abstract»

• ### Nonconvex Compressed Sensing by Nature-Inspired Optimization Algorithms

Publication Year: 2015, Page(s):1042 - 1053
Cited by:  Papers (5)
| | PDF (5465 KB) | HTML Media

The l0regularized problem in compressed sensing reconstruction is nonconvex with NP-hard computational complexity. Methods available for such problems fall into one of two types: greedy pursuit methods and thresholding methods, which are characterized by suboptimal fast search strategies. Nature-inspired algorithms for combinatorial optimization are famous for their efficient global sea... View full abstract»

• ### A New Evolutionary Algorithm with Structure Mutation for the Maximum Balanced Biclique Problem

Publication Year: 2015, Page(s):1054 - 1067
Cited by:  Papers (5)
| | PDF (1858 KB) | HTML

The maximum balanced biclique problem (MBBP), an NP-hard combinatorial optimization problem, has been attracting more attention in recent years. Existing node-deletion-based algorithms usually fail to find high-quality solutions due to their easy stagnation in local optima, especially when the scale of the problem grows large. In this paper, a new algorithm for the MBBP, evolutionary algorithm wit... View full abstract»

• ### Rating Knowledge Sharing in Cross-Domain Collaborative Filtering

Publication Year: 2015, Page(s):1068 - 1082
Cited by:  Papers (8)
| | PDF (1857 KB) | HTML

Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain C... View full abstract»

Publication Year: 2015, Page(s):1083 - 1094
Cited by:  Papers (53)
| | PDF (1599 KB) | HTML

Clustering, as one of the most classical research problems in pattern recognition and data mining, has been widely explored and applied to various applications. Due to the rapid evolution of data on the Web, more emerging challenges have been posed on traditional clustering techniques: 1) correlations among related clustering tasks and/or within individual task are not well captured; 2) the proble... View full abstract»

• ### Active Learning With Imbalanced Multiple Noisy Labeling

Publication Year: 2015, Page(s):1095 - 1107
Cited by:  Papers (13)
| | PDF (1716 KB) | HTML

With crowdsourcing systems, it is easy to collect multiple noisy labels for the same object for supervised learning. This dynamic annotation procedure fits the active learning perspective and accompanies the imbalanced multiple noisy labeling problem. This paper proposes a novel active learning framework with multiple imperfect annotators involved in crowdsourcing systems. The framework contains t... View full abstract»

• ### A Dual-Population Differential Evolution With Coevolution for Constrained Optimization

Publication Year: 2015, Page(s):1108 - 1121
Cited by:  Papers (8)
| | PDF (2027 KB) | HTML

Inspired by the fact that in modern society, team cooperation and the division of labor play important roles in accomplishing a task, this paper proposes a dual-population differential evolution (DPDE) with coevolution for constrained optimization problems (COPs). The COP is treated as a bi-objective optimization problem where the first objective is the actual cost or reward function to be optimiz... View full abstract»

• ### Robust 2DPCA With Non-greedy$\ell _{1}$-Norm Maximization for Image Analysis

Publication Year: 2015, Page(s):1108 - 1112
Cited by:  Papers (24)
| | PDF (334 KB) | HTML

2-D principal component analysis based on ℓ1-norm (2DPCA-L1) is a recently developed approach for robust dimensionality reduction and feature extraction in image domain. Normally, a greedy strategy is applied due to the difficulty of directly solving the ℓ1-norm maximization problem, which is, however, easy to get stuck in local solution. In this paper, we propose a robust 2D... View full abstract»

• ### IEEE Systems, Man, and Cybernetics Society Information

Publication Year: 2015, Page(s): C3
| PDF (106 KB)
• ### IEEE Transactions on Cybernetics information for authors

Publication Year: 2015, Page(s): C4
| PDF (110 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