Trajectory tracking of nonlinear system using multiple series-parallel dynamic neural networks
This paper presents a novel approach of adaptive control for unknown nonlinear continuous-time dynamic system using series-parallel dynamic neural networks (SPDNN) and multiple models. Dynamic neural networks are introduced into the multiple models ...
Passivity analysis of impulsive coupled reaction-diffusion neural networks with and without time-varying delay
In this paper, we respectively investigate the input strict passivity and output strict passivity of impulsive coupled reaction-diffusion neural networks with and without time-varying delay. By constructing suitable Lyapunov functionals and utilizing ...
A robust hybrid method for text detection in natural scenes by learning-based partial differential equations
Learning-based partial differential equations (PDEs), which combine fundamental differential invariants into a non-linear regressor, have been successfully applied to several computer vision tasks. In this paper, we present a robust hybrid method that ...
Lead curve detection in drawings with complex cross-points
Lead curve detection in design drawings is a critical problem in a wide range of applications ranging from checking similar drawings in patent granting to constructing hyperlinks between image and text description in digitalization. The difficulty of ...
Global mutual information-based feature selection approach using single-objective and multi-objective optimization
Feature selection is an important preprocessing step in data mining. Mutual information-based feature selection is a kind of popular and effective approaches. In general, most existing mutual information-based techniques are greedy methods, which are ...
A weakly supervised geodesic level set framework for interactive image segmentation
Interactive image segmentation is growingly useful for selecting objects of interest in images, facilitating spatially localized media manipulation especially on touch screen devices. We present a robust and efficient approach for segmenting image with ...
Neural network control-based adaptive design for a class of DC motor systems with the full state constraints
In the paper, an adaptive neural controller for the tracking problem of a direct-current (DC) motor is investigated. Because the unknown functions are included in the systems, the neural networks are used to estimate the unknown functions. In this study,...
Joint representation and pattern learning for robust face recognition
Image feature is a significant factor for the success of robust face recognition. Recently sparse representation based classifier (SRC) has been widely applied to robust face recognition by using sparse representation residuals to tolerate disturbed ...
Decentralized control for stabilization of nonlinear multi-agent systems using neural inverse optimal control
This paper proposes a decentralized control for stabilization of nonlinear multi-agent systems using neural inverse optimal control. This approach consists in synthesizing a suitable controller for each agent; accordingly, each local subsystem is ...
Multi-label feature selection based on max-dependency and min-redundancy
Multi-label learning deals with data belonging to different labels simultaneously. Like traditional supervised feature selection, multi-label feature selection also plays an important role in data mining, information retrieval, and machine learning. In ...
A novel Bayesian-based nonlocal reconstruction method for freehand 3D ultrasound imaging
Freehand three-dimensional (3D) ultrasound imaging is an important medical imaging modality in computer-assisted clinical diagnosis and image-guided intervention. In this paper, we present a novel Bayesian-based nonlocal method for the accurate volume ...
Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis
Gearboxes are crucial transmission components in mechanical systems. Fault diagnosis is an important tool to maintain gearboxes in healthy conditions. It is challenging to recognize fault existences and, if any, failure patterns in such transmission ...
Training sensory-motor behavior in the connectome of an artificial C. elegans
The Caenorhabditis elegans nematode worm is a small well-known creature, intensely studied for decades. Its entire morphology has been mapped cell-by-cell, including its 302 neuron connectome. The connectome is a synaptic wiring diagram that also ...
Global µ-stability of complex-valued delayed neural networks with leakage delay
In this paper, the global µ-stability is investigated for the complex-valued neural networks with leakage time delay and unbounded time-varying delays. The activation functions considered are no longer required to be derivable. By constructing ...
Nonlinear observer design for PEM fuel cell power systems via second order sliding mode technique
In this paper, a nonlinear observer is proposed for a PEMFC system, based on Second Order Sliding Mode (SOSM) techniques. The goal is to estimate the hydrogen partial pressure in the anode channel of the PEMFC, using the measurements of stack voltage, ...
Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with unknown time-delay
In this paper, an adaptive neural network tracking control is studied for a class of uncertain nonlinear systems. The studied systems are in discrete-time form and unknown time-delay is considered here. Up to now, the research works on nonlinear ...
A work point count system coupled with back-propagation for solving double dummy bridge problem
The game 'contract bridge' is one of the most widely known card games comprising many fascinating aspects, such as bidding, playing and winning the trick including estimation of hand strength, the additional input data based on the human knowledge of ...
Combining eye tracking and pupillary dilation analysis to identify Website Key Objects
Identifying the salient zones from Web interfaces, namely the Website Key Objects, is an essential part of the personalization process that current Web systems perform to increase user engagement. While several techniques have been proposed, most of ...
A local-global mixed kernel with reproducing property
A wide variety of kernel-based methods have been developed with great successes in many fields, but very little research has focused on the reproducing kernel function in Reproducing Kernel Hilbert Space (RKHS). In this paper, we propose a novel method ...
Adaptive fuzzy output-feedback control for a class of nonlinear switched systems with unmodeled dynamics
In this paper, an adaptive fuzzy output tracking control approach is proposed for a class of uncertain nonlinear switched systems with unmeasured states, unknown nonlinear functions, unmodeled dynamics, and dynamical disturbances. In the control design, ...
Mutual information criterion for feature selection from incomplete data
Feature selection is an important preprocessing step in machine learning and data mining, and feature criterion arises a key issue in the construction of feature selection algorithms. Mutual information is one of the widely used criteria in feature ...
An improved radial basis function neural network for object image retrieval
Radial Basis Function Neural Networks (RBFNNs) have been widely used for classification and function approximation tasks. Hence, it is worthy to try improving and developing new learning algorithms for RBFNNs in order to get better results. This paper ...
Efficient Lasso training from a geometrical perspective
The Lasso (L1-penalized regression) has drawn great interests in machine learning and statistics due to its robustness and high accuracy. A variety of methods have been proposed for solving the Lasso. But for large scale problems, the presence of L1 ...
Granular fuzzy modeling with evolving hyperboxes in multi-dimensional space of numerical data
Clustering has been applied to numerous areas, including signal and image processing. Many approaches have been developed over the years to efficiently construct granular models on a basis of numerical experimental data. In this study, we propose a ...
Distributed reference model based containment control of second-order multi-agent systems
This paper addresses the distributed containment control problem in a group of agents governed by second-order sampled-data dynamics with directed network topologies. Based on the assumption on the communication topology between agents, a distributed ...
Cluster synchronization in complex networks of nonidentical dynamical systems via pinning control
In this paper, we investigate the cluster synchronization problem of complex networks via pinning control. Nodes in the same cluster are governed by the same dynamical function, while the functions for different clusters are different. For the coupling ...
Guaranteed cost load frequency control for a class of uncertain power systems with large delay periods
This paper investigates the problem of guaranteed cost load frequency control (LFC) for a class of uncertain power systems with large delay periods (LDPs). The model of LFC for power systems with LDPs has been firstly modeled as a switched delay system, ...
Delay-dependent passivity analysis of impulsive neural networks with time-varying delays
This paper investigates delay-dependent passivity for a class of impulsive neural networks with bounded or unbounded time-varying delays. By applying Lyapunov-Krasovskii functional and matrix inequality approach, some new delay-dependent passivity ...
Improved exponential stability criteria for time-varying delayed neural networks
This paper is concerned with the exponential stability for neural networks with mixed time-varying delays. By using a more general delay-partitioning approach, an augmented Lyapunov functional that contains some information about neuron activation ...
