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The robust exponential stability of uncertain neural networks with time delay is analyzed based on Lyapunov stability theory. The nonlinear uncertain perturbation in the neural networks satisfies the cone bounded condition. By choosing suitable Lyapunov functional, several sufficient conditions on robust stability and robust exponential stability of uncertain neural networks with time delays are given...
Robust lane detection is important to the lane departure warning (LDW) for driver assistant system. In this study, lane marks are extracted by searching the lane model parameters in a special defined parameter space without thresholding. The proposed method is based on the lateral inhibition property of human vision system to clear up the edges of lane marks in variant weather conditions; moreover,...
This paper is concerned with the robust stability problem for a class of structured uncertain stochastic neural networks with discrete and distributed time varying delays. An integral sliding surface is first constructed. The stability criterion is described in terms of linear matrix inequalities (LMIs), which can be easily checked in practice. An adaptive control law is established to guarantee the...
In this paper we propose a novel technique for the corner detection of plane curves. This corner detector is given through the triangle-area representation method, whose underlying idea rests on the maximum property of the local area at the corner point. Therefore, the method can be realized easily and is of high accuracy under some appropriate scale ( triangle-length scale ). The experimental results...
This paper proposes a new adaptive fuzzy active disturbance rejection control design technique on permanent magnet synchronous motor (PMSM). Fuzzy logic control is applied to adjust the proportional coefficient of nonlinear proportional error control (NLPE). The extended state observer (ESO) is used to track and estimate the uncertainty of PMSM system including unmodeled dynamics, load disturbances...
Optical character recognition (OCR) is a very active field for research and development, and has become one of the most successful applications of automatic pattern recognition. To avoid the curse of dimensionality and improve the recognition performance, an optical character recognition system based on image preprocessing technologies combined with least square support vector machine (LS-SVM) has...
This paper addresses the problem of terrain reconstruction for autonomous navigation. Dense stereo matching based terrain reconstruction methods are sensitive to mismatch pixels in disparity map, and consume lots of computation on pixels in uninterested regions. Traditional sample point pre-selection methods (SPPS) are effective, but they can only obtain sparse terrain map for grid-based representation...
One of the main issues of face recognition is to decide what features to represent a face. In this paper, we present a new algorithm that extracts facial features on some fiducial points. 17 fiducial points are automatically located by Active Appearance Models (AAMs) and characterized with Gabor wavelet analysis. The features are evaluated by a face database, which includes more than 400 images of...
In practical problems, the constrained least square constant modulus algorithm (LSCMA) can suffer significant performance degradation in the presence of the slight mismatches between the actual and presumed array responses to the desired signal. In this paper, a novel robust constrained LSCMA is proposed based on explicit modeling of uncertainties in the desired signal array response. The proposed...
Support vector machines (SVMs) have been dominant learning techniques for more than ten years, and mostly applied to supervised learning problems. These years two-class unsupervised and semi-supervised classification algorithms based on bounded C-SVMs, bounded ??-SVMs and Lagrangian SVMs (LSVMs) respectively, which are relaxed to semi-definite programming (SDP), get good classification results. These...
To remove the impulsive noise and preserve the fine pixels in color images, a new switching filter called robust rank vector median filter is proposed. The method determines whether the central vector is replaced in the filtering window by the switching noise detector. The filter has better performance, robustness and low computational requirements. Extensive experiments show the new method yields...
Vibration suppress of a flexible spacecraft during attitude maneuvering is a challenging task. In this paper, the proposed control includes two major parts: command profile is designed to maneuver a flexible spacecraft with very little residual vibration and an intelligent control scheme consists of an online radial basis function neural network(RBFNN) based slide mode control is performed such that...
In this paper, the intelligent internal model control algorithm was applied to a temperature object. According to experimental results it is shown that control performance of the intelligent internal model control algorithm is superior to one of the internal model control algorithm. It has great robustness and anti-inference, and this algorithm makes a small computation which is easy to use for engineering...
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