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This paper considers the problem of block-oriented Wiener systems control. Designing controllers for Wiener systems face many challenges, for instance, parameter uncertainty and lack of state measurement. To address these issues, the input-output response of a class of Wiener systems is represented with a simple fractional-order model, then a closed-loop model reference fractional adaptive controller...
In this paper, we propose a L1-Norm driven Semi-Supervised Local Discriminant Projection (S2LDP-L1) for robust dimensionality reduction and image representation. For feature learning, our S2LDP-L1 approach aims at compacting local within-class divergence and separating local betweenclass divergence at the same time in addition to possessing the locality preserving power over all training data. To...
The parallel algorithm of Petri net based on multi-core clusters is put forward in order to make the Petri net system with concurrent synchronous function realize parallel control and running. First, select different Petri net structures and conduct transformation, and give the partitioning method of the subnets of place invariant-based Petri net system. Then, put forward the parallel algorithm of...
Cloud computing aims at providing services on the basis of a shared pool of underpinning resources and load balancing is of paramount importance in such an environment. At the same time, multi-tenancy is widely adopted in cloud computing to reduce the costs of service provisioning and to improve resource utilization. Multi-tenancy brings new challenges to load balancing, since it incurs resource competition...
Quality assessment of Multiobjective Optimization Evolutionary Algorithms (MOEA) has been a major concern in scientific field during the last few years. The entropy metric is introduced and highlighted in computing the diversity of MOEA. Existing performance metrics are briefly reviewed. The advantages of entropy approach over other diversity metrics are classified here. Besides, the definition of...
It is important to integrate contextual information in order to improve the performance of automatic image annotation. Graph based representations allow incorporation of such information. In this paper, we propose a graph-based approach to automatic image annotation which models both feature similarities and semantic relations in a single graph. The annotation quality is enhanced by introducing graph...
In this paper the servo problem in a 3-D robot manipulator based only on the visual measurements by following the dynamic visual servoing approach with a fixed camera configuration is considered. To model the whole visual servoing system, we consider the robot in an image space, reconstructed from the perspective projection of the robot space in the image plane. The manipulator dynamics is lifted...
Image semantic has the characters of vague and abstractive, therefore, only low-level feature is not enough to describe image semantics. It requires to combine with image related content in order to improve the accuracy of the image annotation In this paper, An image annotation algorithm based on mutual K adjacency graph is proposed which describes the relationship between the low-level features,...
In order to improve the computing speed of automatic image annotation. We propose a fast solution for this problem in this paper. First, the proposed approach describes the relationship between the low-level features, annotated words and image by a multi-modal graph which is linear correlation, block-wise and community-like structure. Second, we, to achieve fast solution of the problem, exploit the...
Here we depart from the standard stabilization objective of adaptive control and assume that for the plant to be controlled a parametrization of the regulator insuring closed-loop stability is known. The structure, dynamic order and number of adjustable parameters of the compensator are at the designer's disposal and no assumptions, except linearity are imposed on the plant. We propose an on-line...
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