Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of ...
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ISBN:
(纸本)9781479938414
Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of Learning Automata to select only the optimal action out of a set of actions, this paper considers a multiple-action selection problem and proposes a novel class of Learning Automata for selecting an optimal subset of actions. Their objective is to identify the optimal subset: the top k out of r actions. Based on conventional continuous pursuit and discretized pursuit learning schemes, this paper introduces four pursuit learning schemes for selecting the optimal subset, called continuous equal pursuit, discretized equal pursuit, continuous unequal pursuit and discretized unequal pursuit learning schemes, respectively. In conjunction with a reward-inaction learning paradigm, the above four schemes lead to four versions of pursuit Learning Automata for selecting the optimal subset. The simulation results present a quantitative comparison between them.
In this paper, we investigate the synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control, where the coupling matrix denoting network topology is assumed to be symmetri...
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ISBN:
(纸本)9781467355339
In this paper, we investigate the synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control, where the coupling matrix denoting network topology is assumed to be symmetric. A sufficient condition to guarantee global synchronization is presented. Moreover, a centralized adaptive intermittent control is designed and its validity is rigorously proved. Finally, some numerical examples are presented to demonstrate the correctness of obtained theoretical results.
In this paper,the cluster synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control is *** first,a sufficient condition to guarantee cluster synchronization is ***,an ada...
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ISBN:
(纸本)9781479900305
In this paper,the cluster synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control is *** first,a sufficient condition to guarantee cluster synchronization is ***,an adaptive intermittent control algorithm is designed to the control strength and its validity is rigorously ***,some numerical examples are presented to demonstrate the correctness of obtained theoretical results.
The real-time traffic parameters are necessary to dynamic traffic light control at intersection due to the serious traffic congestion. In this paper, we describe an approach for the real-time vehicle queue length meas...
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Growth of NaCl and Fe/NaCl/Fe Magnetic tunneling junctions on Si (100) has been achieved by using a high vacuum electron-beam deposition system. Epitaxial tunnel junctions turn out to be prone to pinholes as well as e...
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ISBN:
(纸本)9781479956234
Growth of NaCl and Fe/NaCl/Fe Magnetic tunneling junctions on Si (100) has been achieved by using a high vacuum electron-beam deposition system. Epitaxial tunnel junctions turn out to be prone to pinholes as well as electrode oxidation. Instead, the best tunneling magnetoresistance we have achieved in this system is on polycrystalline tunnel barriers with thin Mg insertion, and reaching 22.3% at room temperature.
The Locality-weight fuzzy c-means clustering method has been presented *** this approach can improve the clustering accuracies,it often gains the unstable clustering results because some random samples are employed fo...
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ISBN:
(纸本)9781467349970
The Locality-weight fuzzy c-means clustering method has been presented *** this approach can improve the clustering accuracies,it often gains the unstable clustering results because some random samples are employed for the initial *** this paper,an initialization method based on the core clusters is used for the locality-weight fuzzy c-means *** core clusters can be formed by constructing the σ-neighborhood graph and their centers are regarded as the initial centers of the locality-weight fuzzy c-means *** investigate the effectiveness of our approach,several experiments are done on three *** results show that our proposed method can improve the clustering performance compared to the previous locality-weight fuzzy c-means clustering.
This paper proposes a method of the fault detection and diagnosis for the railway turnout based on the current curve of switch machine. Exact curve matching fault detection method and SVM-based fault diagnosis method ...
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This paper proposes a two-dimensional color uncorrelated principal component analysis algorithm(2DCUPCA) for unsupervised subspace learning directly from color face images. The 2DCUPCA can be used to explore uncorrela...
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Based on principal component analysis (PCA) and support vector machine (SVM), a new method for the fault diagnosis of TE Process is proposed. The fault recognition based on kernel principal component analysis (KPCA) i...
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ISBN:
(纸本)9781479970063
Based on principal component analysis (PCA) and support vector machine (SVM), a new method for the fault diagnosis of TE Process is proposed. The fault recognition based on kernel principal component analysis (KPCA) is analyzed and SVM is employed as a classifier for fault classification. To establish a more efficient SVM model, genetic algorithm (GA) is used to determine the optimal kernel parameter γ and penalty parameter C of SVM with the highest accuracy and generalization ability. The classification accuracy of this GA-SVM approach is tested by real data of TE Process and compared with some other related methods such as artificial neural network. The experimental results indicate that the classification accuracy of this GA-SVM is more superior than that of some artificial neural network.
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