IEEE Transactions on Cybernetics

An innovative simulated evolutionary algorithm (EA), called I-Ching divination EA (IDEA), and its convergence analysis are proposed and investigated in this paper. Inherited from ancient Chinese culture, I-Ching divination has always been used as a divination system in traditional and modern China. There are three operators evolved from I-Ching transformations in this new optimization algorithm, i... View full abstract»

How can we find a general way to choose the most suitable samples for training a classifier? Even with very limited prior information? Active learning, which can be regarded as an iterative optimization procedure, plays a key role to construct a refined training set to improve the classification performance in a variety of applications, such as text analysis, image recognition, social network mode... View full abstract»

Sparse coding has been widely applied to learning-based single image super-resolution (SR) and has obtained promising performance by jointly learning effective representations for low-resolution (LR) and high-resolution (HR) image patch pairs. However, the resulting HR images often suffer from ringing, jaggy, and blurring artifacts due to the strong yet ad hoc assumptions that the LR image patch r... View full abstract»

Domain adaptation learning (DAL) investigates how to perform a task across different domains. In this paper, we present a kernelized local-global approach to solve domain adaptation problems. The basic idea of the proposed method is to consider the global and local information regarding the domains (e.g., maximum mean discrepancy and intraclass distance) and to convert the domain adaptation proble... View full abstract»

The bias feature is a major factor that makes a multiobjective optimization problem (MOP) difficult for multiobjective evolutionary algorithms (MOEAs). To deal with this problem feature, an algorithm should carefully balance between exploration and exploitation. The decomposition-based MOEA decomposes an MOP into a number of single objective subproblems and solves them in a collaborative manner. S... View full abstract»

Reliability estimation is central to enhance safety, availability, and effectiveness of phased-mission systems (PMSs). With the development of information and sensing technologies, condition monitoring (CM) data are now available in many real-world PMSs, and then a more interesting question: how can we dynamically estimate the reliability of PMSs using the in-situ CM data, is of considerable signi... View full abstract»

“Big data” is an emerging topic and has attracted the attention of many researchers and practitioners in industrial systems engineering and cybernetics. Big data analytics would definitely lead to valuable knowledge for many organizations. Business operations and risk management can be a beneficiary as there are many data collection channels in the related industrial systems (e.g., wireless sensor... View full abstract»

This paper addresses the problem of target detection in dynamic environments in a semi-supervised data-driven setting with low-cost passive sensors. A key challenge here is to simultaneously achieve high probabilities of correct detection with low probabilities of false alarm under the constraints of limited computation and communication resources. In general, the changes in a dynamic environment ... View full abstract»

In this paper, we consider the cooperative output regulation problem of heterogeneous linear multi-agent systems (MASs) by event-triggered control. We first develop an event-triggering mechanism for leader-following consensus of homogeneous MASs. Then by proposing an internal reference model for each agent, a novel distributed event-triggered control scheme is developed to solve the cooperative ou... View full abstract»

Object detection is an important task in computer vision and machine intelligence systems. Multistage particle windows (MPW), proposed by Gualdi et al., is an algorithm of fast and accurate object detection. By sampling particle windows (PWs) from a proposal distribution (PD), MPW avoids exhaustively scanning the image. Despite its success, it is unknown how to determine the number of stages and t... View full abstract»

In this paper, the problem of output synchronization is investigated for the heterogeneous network with an uncertain leader. It is assumed that parameter perturbations influence the nonidentical linear agents, whose outputs are controlled to track the output of an uncertain leader. Based on the hierarchical structure of the communication graph, a novel control scheme is proposed to guarantee the o... View full abstract»

This paper presents a half-face dictionary integration (HFDI) algorithm for representation-based classification. The proposed HFDI algorithm measures residuals between an input signal and the reconstructed one, using both the original and the synthesized dual-column (row) half-face training samples. More specifically, we first generate a set of virtual half-face samples for the purpose of training... View full abstract»

This paper is concerned with the problem of asynchronous H∞filtering for a class of discrete-time Takagi-Sugeno fuzzy affine systems against time-varying signal transmission delays and measurement quantization. The asynchrony refers to the situation that the plant state and the filter state belong to different local state space regions, and the quantization density can be adjusted to sa... View full abstract»

High-risk drinking is considered a major concern in public health, being the third leading preventable cause of death in the United States. Several studies have been conducted to understand the etiology of high-risk drinking and to design prevention strategies to reduce unhealthy alcohol-consumption and related problems, but there are still major gaps in identifying and investigating the key compo... View full abstract»

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the c... View full abstract»

In the past two decades, unmanned aerial vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, where tasks can be dull, dirty, dangerous, or simply too costly with conventional methods. Many of the applications contain tasks that can be executed in parallel, hence the natural progression is to deploy multiple UAVs working together as a force multip... View full abstract»

Dynamic multiobjective optimization (DMO) has received growing research interest in recent years since many real-world optimization problems appear to not only have multiple objectives that conflict with each other but also change over time. The time-varying characteristics of these DMO problems (DMOPs) pose new challenges to evolutionary algorithms. Considering the importance of a representative ... View full abstract»

This paper investigates the leader-following consensus for multiagent systems with general linear dynamics by means of event-triggered scheme (ETS). We propose three types of schemes, namely, distributed ETS (distributed-ETS), centralized ETS (centralized-ETS), and clustered ETS (clustered-ETS) for different network topologies. All these schemes guarantee that all followers can track the leader ev... View full abstract»

Ever-increasing size and complexity of data sets create challenges and potential tradeoffs of accuracy and speed in learning algorithms. This paper offers progress on both fronts. It presents a mechanism to train the unsupervised learning features learned from only one layer to improve performance in both speed and accuracy. The features are learned by an unsupervised feature learning (UFL) algori... View full abstract»

Numerous state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage process: distortion description followed by distortion effects pooling. As for the first stage, the distortion descriptors or measurements are expected to be effective representatives of human visual variations, while the second stage should well express the relationship among quality descriptor... View full abstract»

Differential evolution (DE) is a simple but powerful evolutionary algorithm, which has been widely and successfully used in various areas. In this paper, an event-triggered impulsive (ETI) control scheme is introduced to improve the performance of DE. Impulsive control (IPC), the concept of which derives from control theory, aims at regulating the states of a network by instantly adjusting the sta... View full abstract»

This paper addresses the partial synchronization problem for the interconnected Boolean networks (BNs) via the semi-tensor product (STP) of matrices. First, based on an algebraic state space representation of BNs, a necessary and sufficient criterion is presented to ensure the partial synchronization of the interconnected BNs. Second, by defining an induced digraph of the partial synchronized stat... View full abstract»