IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

In this paper, a novel constructive-optimizer neural network (CONN) is proposed for the traveling salesman problem (TSP). CONN uses a feedback structure similar to Hopfield-type neural networks and a competitive training algorithm similar to the Kohonen-type self-organizing maps (K-SOMs). Consequently, CONN is composed of a constructive part, which grows the tour and an optimizer part to optimize ... View full abstract»

A novel image-mosaicking technique suitable for 3D visualization of roadside buildings on Web sites or mobile systems is proposed. Our method was tested on a roadside building scene taken using a side-looking video camera employing a continuous set of vertical-textured planar faces. A vertical plane approximation of the scene geometry for each frame was calculated using sparsely distributed featur... View full abstract»

Output-time prediction is a critical task to a wafer fab. To further enhance the accuracy of wafer-lot output-time prediction, the concept of input classification is applied to Chen's fuzzy backpropagation network (FBPN) approach in this paper by preclassifying wafer lots with the fuzzy c-means (FCM) classifier before predicting the output times. In this way, similar wafer lots are clustered in th... View full abstract»

Artificial neural networks (ANNs) are a powerful and widely used pattern recognition technique. However, they remain "black boxes" giving no explanation for the decisions they make. This paper presents a new algorithm for extracting a logistic model tree (LMT) from a neural network, which gives a symbolic representation of the knowledge hidden within the ANN. Landwehr's LMTs are based on standard ... View full abstract»

In order to monitor sufficiently large areas of interest for surveillance or any event detection, we need to look beyond stationary cameras and employ an automatically configurable network of nonoverlapping cameras. These cameras need not have an overlapping field of view and should be allowed to move freely in space. Moreover, features like zooming in/out, readily available in security cameras th... View full abstract»

The use of natural language rules that are able to handle vague and, possibly, even contradicting knowledge in order to model formal dependences is an intriguing idea. Fuzzy if-then rules have been proposed as classification methods that can easily be defined and interpreted by humans or built automatically by learning algorithms. This paper gives an intuitive insight into the properties and the b... View full abstract»

Fuzzy time-series models have been widely applied due to their ability to handle nonlinear data directly and because no rigid assumptions for the data are needed. In addition, many such models have been shown to provide better forecasting results than their conventional counterparts. However, since most of these models require complicated matrix computations, this paper proposes the adoption of a ... View full abstract»

This paper addresses the problem of automatically tuning multiple kernel parameters for the kernel-based linear discriminant analysis (LDA) method. The kernel approach has been proposed to solve face recognition problems under complex distribution by mapping the input space to a high-dimensional feature space. Some recognition algorithms such as the kernel principal components analysis, kernel Fis... View full abstract»

This paper presents a discrete learning controller for vision-guided robot trajectory imitation with no prior knowledge of the camera-robot model. A teacher demonstrates a desired movement in front of a camera, and then, the robot is tasked to replay it by repetitive tracking. The imitation procedure is considered as a discrete tracking control problem in the image plane, with an unknown and time-... View full abstract»

We present a new speech enhancement scheme for a single-microphone system to meet the demand for quality noise reduction algorithms capable of operating at a very low signal-to-noise ratio. A psychoacoustic model is incorporated into the generalized perceptual wavelet denoising method to reduce the residual noise and improve the intelligibility of speech. The proposed method is a generalized time-... View full abstract»

In the near future, autonomous mobile robots are expected to help humans by performing service tasks in many different areas, including personal assistance, transportation, cleaning, mining, or agriculture. In order to manage these tasks in a changing and partially unpredictable environment without the aid of humans, the robot must have the ability to plan its actions and to execute them robustly ... View full abstract»

This paper presents a new stochastic algorithm for solving hierarchical multiobjective optimization problems. The algorithm is based on the simulated annealing concept and returns a single solution that corresponds to the lexicographic ordering approach. The algorithm optimizes simultaneously the multiple objectives by assigning a different initial temperature to each one, according to its positio... View full abstract»

In this paper, the robust Hinfin control problem Is considered for a class of networked systems with random communication packet losses. Because of the limited bandwidth of the channels, such random packet losses could occur, simultaneously, in the communication channels from the sensor to the controller and from the controller to the actuator. The random packet loss is assumed to obey the Bernoul... View full abstract»

This paper presents several results on some cost-minimizing path problems in polygonal regions. For these types of problems, an approach often used to compute approximate optimal paths is to apply a discrete search algorithm to a graph Gepsi constructed from a discretization of the problem; this graph is guaranteed to contain an epsi-good approximate optimal path, i.e., a path with a co... View full abstract»

The common vector (CV) method is a linear subspace classifier method which allows one to discriminate between classes of data sets, such as those arising in image and word recognition. This method utilizes subspaces that represent classes during classification. Each subspace is modeled such that common features of all samples in the corresponding class are extracted. To accomplish this goal, the m... View full abstract»

Bayesian networks (BNs) and influence diagrams (IDs) are probabilistic graphical models that are widely used for building diagnosis- and decision-support expert systems. Explanation of both the model and the reasoning is important for debugging these models, alleviating users' reluctance to accept their advice, and using them as tutoring systems. This paper describes some explanation options for B... View full abstract»

The U.S. Department of Health and Human Services human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) treatment guidelines are modified several times per year to reflect the rapid evolution of the field (e.g., emergence of new antiretroviral drugs). As such, a treatment- decision support system that is capable of self-learning is highly desirable. Based on the fuzzy discre... View full abstract»

To replace compromised biometric templates, cancelable biometrics has recently been introduced. The concept is to transform a biometric signal or feature into a new one for enrollment and matching. For making cancelable fingerprint templates, previous approaches used either the relative position of a minutia to a core point or the absolute position of a minutia in a given fingerprint image. Thus, ... View full abstract»

In this paper, we analyze from a geometric perspective the meaningful relations taking place between belief and probability functions in the framework of the geometric approach to the theory of evidence. Starting from the case of binary domains, we identify and study three major geometric entities relating a generic belief function (b.f.) to the set of probabilities P: 1) the dual line connecting ... View full abstract»

In this correspondence, we propose a wavelet-based hierarchical approach using mutual information (MI) to solve the correspondence problem in stereo vision. The correspondence problem involves identifying corresponding pixels between images of a given stereo pair. This results in a disparity map, which is required to extract depth information of the relevant scene. Until recently, mostly correlati... View full abstract»

The literature on independent component analysis (ICA)-based face recognition generally evaluates its performance using standard principal component analysis (PCA) within two architectures, ICA Architecture I and ICA Architecture II. In this correspondence, we analyze these two ICA architectures and find that ICA Architecture I involves a vertically centered PCA process (PCA I), while ICA Architec... View full abstract»

This correspondence presents a two-stage classification learning algorithm. The first stage approximates the class-conditional distribution of a discrete space using a separate mixture model, and the second stage investigates the class posterior probabilities by training a network. The first stage explores the generative information that is inherent in each class by using the Chow-Liu (CL) method,... View full abstract»

This correspondence studies the problem of observer-based Hinfin control for time-delay Takagi-Sugeno (T-S) fuzzy systems. It provides a delay-dependent linear matrix inequality (LMI)-based method for the control design. It is known that the key important problem in the literature, even for delay-independent case, lies in the difficulty of decoupling matrix variables in corresponding ma... View full abstract»