This paper considers the problem of using an integral sliding mode strategy to reduce the disturbance terms acting on nonlinear systems in regular form. It is proved that the definition of a suitable sliding manifold ...
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This paper deals with the problem of numerical analysis of multidimensional systems with interval parameters in relation to the operability of MIMO systems. The problem is analyzed for the case when the relative estim...
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ISBN:
(纸本)9789604741991
This paper deals with the problem of numerical analysis of multidimensional systems with interval parameters in relation to the operability of MIMO systems. The problem is analyzed for the case when the relative estimation of the interval parameters exceeds 0.5 and based on the assumption that only the state matrix of a MIMO system contains interval parameters. The problem of operability estimation of the MIMO system is solved with interval degeneration factors. Interval degeneration factors are constructed using interval arithmetic and the singular values of the interval criterion matrices of the system. An operability analysis algorithm of multidimensional systems with interval parameters is proposed in the paper. The results are supported with an example.
In this paper, we present an investigation into the performance of conformal predictors for discriminating the aroma of different types of tea using an electronic nose system based on gas sensors. We propose a new non...
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Randić et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and ...
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Randić et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and prove that the claim is correct, and that it also avoids degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the spectral representation. The method adopts M value to characterize a graphical representation and uses 24-component vector as descriptor. The approach is illustrated on the complete coding sequence of beta-globin genes from 7 different species.
This article deals with noise reduction in modern communication systems. Primarily it focuses on cases where conventional filtering techniques based on linear filtering fail. It is modern based approach to adaptive fi...
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This article deals with noise reduction in modern communication systems. Primarily it focuses on cases where conventional filtering techniques based on linear filtering fail. It is modern based approach to adaptive filtering. The article presents a comprehensive hardware and software solutions to the adaptive system using the two main leaders of adaptive LMS (least mean square) and RLS (recursive least squares) algorithms. Adaptive system for noise reduction in radio (mobile) communication is designed in Matlab. This system has its practical use in communication especially in noisy environments (transport, factories, sporting events, etc.).
Robustness of a program is the degree of system correctness of all parts. Measuring robustness is a goal for many researchers. In this paper, program slicing is used to build a robustness hierarchy, where this hierarc...
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Robustness of a program is the degree of system correctness of all parts. Measuring robustness is a goal for many researchers. In this paper, program slicing is used to build a robustness hierarchy, where this hierarchy will be used to test, and build a robust program.
Fuzzy C-Means(FCM) algorithm is one of the most popular methods for image segmentation, but it is in essence a technology of searching local optimal solution. The algorithm's initial clustering centers are the sto...
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Fuzzy C-Means(FCM) algorithm is one of the most popular methods for image segmentation, but it is in essence a technology of searching local optimal solution. The algorithm's initial clustering centers are the stochastic selection which causes it to depend on the selection of the initial cluster centers excessively. It always converges at the local optimum and is sensitive to noise. In order to overcome those defects, the fuzzy C-means cluster segmentation algorithm based on hybridized particle swarm optimization is proposed in this paper. Firstly, the hybridized particle swarm algorithm is used to get the initial cluster centers. Then, the images are segmented using standard FCM algorithm. Experimental results show that the proposed algorithm used for image segmentation can segment images more effectively and can provide more robust segmentation results.
The hybrid minimum principle (HMP) gives necessary conditions to be satisfied for optimal solutions of a hybrid dynamical system. In particular, the HMP accounts for autonomous switching between discrete states that o...
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ISBN:
(纸本)9781424477456
The hybrid minimum principle (HMP) gives necessary conditions to be satisfied for optimal solutions of a hybrid dynamical system. In particular, the HMP accounts for autonomous switching between discrete states that occurs whenever the trajectory hits switching manifolds. In this paper, the existing HMP is extended for hybrid systems with partitioned state space to provide necessary conditions for optimal trajectories that pass through an intersection of switching manifolds. This extension is especially useful for the numerical solution of hybrid optimal control problems as it allows for algorithms with significant reduction of computational complexity. Algorithms based on previous versions of the HMP solve separate optimal control problems for each possible sequence of discrete states. The extension enables us to consider the optimal sequence as subject of optimal control that is varied and finally determined during a single optimization run. A first numerical result illustrates the effectiveness of an algorithm based on the extended HMP.
The fuzzy c-means (FCM) algorithm has been applied in a variety of medical image segmentation applications. The conventional FCM algorithm uses the greylevel information at a single pixel as the feature space and this...
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The fuzzy c-means (FCM) algorithm has been applied in a variety of medical image segmentation applications. The conventional FCM algorithm uses the greylevel information at a single pixel as the feature space and this contains no spatial contextual information, which makes it very sensitive to noise and intensity inhomogeneities. Recently, some modified FCM algorithms with spatial constraints have been published. However, these have individual disadvantages and are not robust enough with different types of noise. In this paper, we propose a modified FCM algorithm incorporating local spatial and intensity information based on an adaptive local window filter whose weighting coefficients differentiate the neighbouring pixels within the local window. Fast clustering is afterwards performed on the intensity histogram of the filtered image. To demonstrate the robustness and insensitivity to noise of the proposed algorithm, it is extensively tested using synthetic images corrupted by a variety of noise. The experimental results are quantitatively evaluated and compared. This algorithm is then applied to mammographic images for breast tissue density segmentation. The segmentation results indicate its effectiveness to the presence of intensity inhomogeneities in mammograms from different density categories.
An algorithm for hybrid optimal control is proposed that varies the discrete state sequence based on gradient information during the search for an optimal trajectory. The algorithm is developed for hybrid systems with...
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ISBN:
(纸本)9781424477456
An algorithm for hybrid optimal control is proposed that varies the discrete state sequence based on gradient information during the search for an optimal trajectory. The algorithm is developed for hybrid systems with partitioned state space. It uses a version of the hybrid minimum principle that allows optimal trajectories to pass through intersections of switching manifolds, which enables the algorithm to vary the sequence. Consequently, the combinatorial complexity of former algorithms can be avoided, since not each possible sequence has to be investigated separately anymore. The convergence of the algorithm is proven and a numerical example demonstrates the efficiency of the algorithm.
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