In this paper a novel class of filters designed for the removal of impulsive noise in color images is presented. The proposed filter class is based on the nonparametric estimation of the density probability function i...
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Parameter estimation of an autoregressive movmg average (ARMA) model is discussed in this paper by using bounding approach. Bounds on the model structure error are assumed unknown, or known but conservative. To reduce...
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Parameter estimation of an autoregressive movmg average (ARMA) model is discussed in this paper by using bounding approach. Bounds on the model structure error are assumed unknown, or known but conservative. To reduce this conservatism, a point-parametric model concept is proposed, where there exist a set of model parameters and structure error corresponding to each input. Feasible parameter sets are defined for point-parametric model. Bounded values on the model parameters and structure error can then be computed jointly by tightening the feasible set using observations under deliberately designed input excitations. Finally, a constantly bounded parameter model is established, which can be used for robust control.
The rapid growth of image archives increases the need for efficient and fast tools that can retrieve and search through a large amount of visual data. In this paper, we propose an efficient method of extracting the im...
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The rapid growth of image archives increases the need for efficient and fast tools that can retrieve and search through a large amount of visual data. In this paper, we propose an efficient method of extracting the image color content, which serves as an image digital signature, allowing us to efficiently index and retrieve the content of large, heterogeneous multimedia Internet based databases. We apply the proposed method for the retrieval of images from the WEBMUSEUM Internet database, containing a collection of fine art images and show that the new method of image color representation is robust to image distorsions caused by resizing and compression and can be incorporated into existing retrieval systems which exploit the information on color content in digital images.
In this paper a novel class of filters designed for the removal of impulsive noise in color images is presented. The proposed filter class is based on the nonparametric estimation of the density probability function i...
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In this paper a novel class of filters designed for the removal of impulsive noise in color images is presented. The proposed filter class is based on the nonparametric estimation of the density probability function in a sliding filter window. The obtained results show good noise removal capabilities and excellent structure preserving properties of the new impulsive noise removal technique.
It is known that over one-third of protein structures contain metal ions, and they are the necessary elements in life system. Traditionally, structural biologists used to investigate properties of metalloproteins (pro...
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We present the results of an experimental investigation that uses two different techniques for controlling a shallow cavity flow in the Mach number range 0.25-0.5. The first method is basically an open-loop design tha...
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ISBN:
(纸本)9781624100307
We present the results of an experimental investigation that uses two different techniques for controlling a shallow cavity flow in the Mach number range 0.25-0.5. The first method is basically an open-loop design that relies on zero-net-mass forcing at an optimal frequency for suppressing the cavity flow resonance. The second method is a parallel-proportional with time delay controller, a linear control design that relies on real-time feedback from the flow to counteract the resonance. With properly tuned parameters, both methods are successful in reducing the cavity resonance for flows in the Mach number range explored. However the parallel-proportional controller exhibits a superior robustness with respect to departure of the Mach number from the design conditions, a signature of feedback control designs that are naturally more capable to handle changes of the open-loop plant. An additional benefit of the feedback control method is the lower power requirement to achieve comparable suppression of the resonance. An interpretation is presented of the physical mechanisms by which the optimal forcing frequency and the parallel-proportional with time delay controller reduce the cavity flow resonance. The results support the idea that the optimal forcing frequency control induces in the system a rapid switching between modes competing for the available energy that can be extracted from the mean flow. In the case of parallel- proportional control mode switching is also observed which involves a larger range of frequencies and spreads more the extracted energy thus producing a flow with a quieter, more broadband spectral signature.
This paper builds on the model and results of T. Basar and R. Srikant, (2002) and extends them to the case of differentiated prices, again for the single link case. It introduces a hierarchical network game with one s...
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This paper builds on the model and results of T. Basar and R. Srikant, (2002) and extends them to the case of differentiated prices, again for the single link case. It introduces a hierarchical network game with one service provider and multiple users of different types, where the service provider is allowed to charge different prices to users of different types. The service provider plays with the users a Stackelberg (leader-follower) game, while among users themselves, they play a Nash game. The paper establishes for a general network with multiple links the existence of a unique Nash equilibrium along with the existence of a unique Stackelberg solution. The economics of providing large capacity and price differentiation is examined especially in the single link case and for a many-user regime. One important result is that optimum price differentiation leads to a more egalitarian distribution of resources at fairer prices and improves the service provider's revenue and network performance. Moreover, the service provider has an incentive to increase the capacity proportionally with the number of additional users admitted.
The article discusses with the utilization of the UML language for project, realization and optimization of distributed control systems. The work is oriented on the part of distributed control system with embedded sys...
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The article discusses with the utilization of the UML language for project, realization and optimization of distributed control systems. The work is oriented on the part of distributed control system with embedded systems interconnected by the industrial bus CAN. The article describes the project methodology, UML model and optimization of the system according to the target function. Also example of using methodology in the KUPSON Electronic Article Surveillance control System is described.
This paper investigates the robustness of dual-rate MPC systems with a proposed inferential control strategy. It shows that for some scenarios where a high-frequency model plant mismatch is presented, such dual-rate i...
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This paper investigates the robustness of dual-rate MPC systems with a proposed inferential control strategy. It shows that for some scenarios where a high-frequency model plant mismatch is presented, such dual-rate inferential MPC systems may be more robust than fast single rate MPC systems.
Magnetic resonance imaging (MRI) is a widely used approach to obtaining high quality medical images of the brain. Post-processing MRI images with segmentation algorithms enhances the visualization and measurement of s...
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ISBN:
(纸本)188933524X
Magnetic resonance imaging (MRI) is a widely used approach to obtaining high quality medical images of the brain. Post-processing MRI images with segmentation algorithms enhances the visualization and measurement of soft tissues and lesions. Segmented brain images contain information amenable to quantitative analysis (e.g., tissue component percentage in a region of interest (ROI)) and diagnostic interpretation (e.g., total lesion volume). A number of different segmentation algorithms have been developed for this purpose. In this paper, we propose a novel automated segmentation technique, hierarchical structure weighted probabilistic neural network (HSWPNN), based on multi-scale feature extraction, hierarchical labeling structure, and a modified weighted probabilistic neural network (PNN). Compared to other clustering algorithms, our method is relatively robust to noise and accurate. We compare our results to a model of ground truth.
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