Fuzzy Cognitive Maps (FCM) is a soft computing, modeling methodology for complex systems, which is originated from the combination of fuzzy logic and neural networks. Many different learning algorithms have been sugge...
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This paper introduces a new approach to statistical pressure snakes. It uses statistical modeling for both object and background to obtain a more robust pressure model. The Expectation Maximization (EM) algorithm is u...
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This paper addresses the development of an adaptive control system for keyhole arc welding process. The system developed adjusts the amperage of the peak current to achieve the desired peak current period under varyin...
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This papers presents CIRES, a new online system for content-based retrieval in digital image libraries. Content-based image retrieval systems have traditionally used color and texture analyses. These analyses have not...
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ISBN:
(纸本)9810474806
This papers presents CIRES, a new online system for content-based retrieval in digital image libraries. Content-based image retrieval systems have traditionally used color and texture analyses. These analyses have not always achieved adequate level of performance and user satisfaction. The growing need for robust image retrieval systems has led to a need for additional retrieval methodologies. CIRES addresses this issue by using image structure in addition to color and texture. The efficacy of using structure in combination with color and texture is demonstrated.
A fundamental problem in computervision is the issue of shape ambiguity. Simply stated, a silhouette cannot uniquely identify an object or an object's classification since many unique objects can present identica...
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A fundamental problem in computervision is the issue of shape ambiguity. Simply stated, a silhouette cannot uniquely identify an object or an object's classification since many unique objects can present identical occluding contours. This problem has no solution in the general case for a monocular vision system. This paper presents a method for disambiguating objects during silhouette matching using a visual servoing system. This method identifies the camera motion(s) that gives disambiguating views of the objects. These motions are identified through a new technique called contour migration. The occluding contour's shape is used to identify objects or object classes that are potential matches for that shape. A contour migration is then determined that disambiguates the possible matches by purposive viewpoint adjustment. The technique is demonstrated using an example set of objects.
作者：
W. Abd-AlmageedC.E. SmithRobotics
Artificial Intelligence and Vision Laboratory Electrical and Computer Engineering Department University of New Mexico Albuquerque NM USA
This paper introduces a new approach to statistical pressure snakes. It uses statistical modeling for both object and background to obtain a more robust pressure model. The Expectation Maximization (EM) algorithm is u...
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This paper introduces a new approach to statistical pressure snakes. It uses statistical modeling for both object and background to obtain a more robust pressure model. The Expectation Maximization (EM) algorithm is used to model the data into a Mixture of Gaussians (MoG). Bayesian theory is then employed as a decision making mechanism. Experimental results using the traditional pressure model and the new mixture pressure model demonstrate the effectiveness of the new models.
This paper addresses the development of an adaptive control system for keyhole arc welding process. The system developed adjusts the amperage of the peak current to achieve the desired peak current period under varyin...
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This paper addresses the development of an adaptive control system for keyhole arc welding process. The system developed adjusts the amperage of the peak current to achieve the desired peak current period under varying manufacturing conditions. A nominal model is selected from models identified using experimental data and is used as the a prior model of the controlled process. A predictive control algorithm has been designed for the nominal model structure. Closed-loop control experiments have been conducted to verify the effectiveness of the developed system under varying set-point and varying travel speed.
In any measuring system the categorization of the error generation factors leads to simplification of complex error problems and to higher suppression of the error. In this paper we categorize, quantify and analyze th...
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In this paper, a robust nonlinear dynamic controller is designed to achieve global practical stabilization for position tracking error of a voltage-fed permanent-magnet stepper motor. The control design is an output-f...
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In this paper, a robust nonlinear dynamic controller is designed to achieve global practical stabilization for position tracking error of a voltage-fed permanent-magnet stepper motor. The control design is an output-feedback design that utilizes only rotor position measurement. Rotor velocity and stator phase currents are not available for feedback. Furthermore, only upper and lower bounds are required for the electromechanical parameters of the motor. The proposed controller is robust to load torques, friction, cogging forces, and other disturbances satisfying certain bounds. These results can also be extended to other classes of motors.
We propose a global high-gain scaling based observer/controller for systems in the uncertain generalized output-feedback canonical form. Time-varying nonlinear parametric uncertainty is allowed to occur coupled with u...
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We propose a global high-gain scaling based observer/controller for systems in the uncertain generalized output-feedback canonical form. Time-varying nonlinear parametric uncertainty is allowed to occur coupled with unmeasured states in the system dynamics. This represents a significant generalization from existing results which allow unknown parameters only in output-dependent terms. This restriction in previous results is mainly owing to the fact that no general solution is known for systems involving bilinear terms in unmeasured states. The design utilizes the dual architecture of a high-gain observer and controller with the underlying state scaling being dynamically output-dependent. The proposed observer/controller structure provides a globally asymptotically stabilizing output-feedback solution for the benchmark open problem proposed in our earlier work with the provision that a magnitude bound on the unknown parameter be given.
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