This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorizati...
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This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorization by total variation constraint and graph *** main contributions of our work are the ***,total variation is incorporated into NMF to control the diffusion *** purpose is to denoise in smooth regions and preserve features or details of the data in edge regions by using a diffusion coefficient based on gradient ***,we add graph regularization into NMF to reveal intrinsic geometry and structure information of features to enhance the discrimination ***,the multiplicative update rules and proof of convergence of the TV-GNMF algorithm are *** conducted on datasets show that the proposed TV-GNMF method outperforms other state-of-the-art algorithms.
Sparse signal recovery deals with finding the sparest solution of an under-determined linear system x = Qs. In this paper, we propose a novel greedy approach to addressing the challenges from such a problem. Such an a...
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This paper present the development a model for obtaining a coagulant for the process of cleaning and discoloration of industrial waste water and the development of a PID automated system for wastewater treatment. The ...
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This paper presents an original theoretical and implementation framework of fractional order event-based control with the purpose of quality improvement at the end production line of a continuous casting process. A re...
This paper presents an original theoretical and implementation framework of fractional order event-based control with the purpose of quality improvement at the end production line of a continuous casting process. A real-life steel manufacturing plant is taken into consideration in the study. A prior fractional order model is considered to tune a fractional order Proportional Integral controller that ensures an ideal flow velocity of liquid steel. A novel event-based fractional order methodology is proposed that uses internal and external process events in order to improve quality . The implementation strategy takes into consideration available software and hardware components at the plant site, offering a realistic and implementable solution, highly suitable for the current steel industry setting. Numeric simulations successfully validate the proposed methodology.
Improving the efficiency of home energy management (HEM) is of great significance to reduce resource waste and to prompt the consumption of renewable energy. With this advanced HEM system, the development of internet-...
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Finding Nash equilibria in non-cooperative games can be, in general, an exceptionally challenging task. This is owed to various factors, including but not limited to the cost functions of the game being nonconvex/nonc...
Finding Nash equilibria in non-cooperative games can be, in general, an exceptionally challenging task. This is owed to various factors, including but not limited to the cost functions of the game being nonconvex/nonconcave, the players of the game having limited information about one another, or even due to issues of computational complexity. The present tutorial draws motivation from this harsh reality and provides methods to approximate Nash or min-max equilibria in non-ideal settings using both optimization- and learning-based techniques. The tutorial acknowledges, however, that such techniques may not always converge, but instead lead to oscillations or even chaos. In that respect, tools from passivity and dissipativity theory are provided, which can offer explanations about these divergent behaviors. Finally, the tutorial highlights that, more frequently than often thought, the search for equilibrium policies is simply vain; instead, bounded rationality and non-equilibrium policies can be more realistic to employ owing to some players’ learning imperfectly or being relatively naive – "bounded rational." The efficacy of such plays is demonstrated in the context of autonomous driving systems, where it is explicitly shown that they can guarantee vehicle safety.
This paper investigates the distributed feedback optimization problem of nonlinear multi-agent systems. In such systems, each agent can measure the relative outputs between itself and its neighbors but lacks access to...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
This paper investigates the distributed feedback optimization problem of nonlinear multi-agent systems. In such systems, each agent can measure the relative outputs between itself and its neighbors but lacks access to their absolute states and internal controller states. By combining distributed optimization and singular perturbation methods, a novel distributed controller design is presented, that relies solely on each agent's real-time gradient values of its local objective function and its relative output measurements to neighboring agents. The boundedness of the closed-loop signals and the convergence of the agent outputs to the minimizer of the total cost are proved rigorously. A numerical example is conducted to validate the effectiveness of the proposed approach.
In this paper, we propose the first framework that enables solving graph learning tasks of all levels (node, edge and graph) and all types (generation, regression and classification) using one formulation. We first fo...
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Factor graphs are graphical models used to represent a wide variety of problems across robotics, such as Structure from Motion (SfM), Simultaneous Localization and Mapping (SLAM) and calibration. Typically, at their c...
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This paper investigates the results of simulations devoted to the acoustic field variation caused by different boundary conditions applied to the backscattering of the acoustic wave in both low and moderately low freq...
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