Classical linear dimensional reduction algorithms, such as Linear Discriminant Analysis (LDA) and Locality Preserving Projections (LPP) have been widely used in computer vision and pattern recognition. However, when d...
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Classical linear dimensional reduction algorithms, such as Linear Discriminant Analysis (LDA) and Locality Preserving Projections (LPP) have been widely used in computer vision and pattern recognition. However, when dealing with the multidimensional dataset, they usually first transform the original data to vectors, and then analyze the data in such a high dimensional space. This process inevitably results in some obvious disadvantages. This paper proposes a novel two-dimensional dimensionality reduction algorithm called 2D Neighborhood Discriminant Projection (2D-NDP), which is based directly on 2D image matrices rather than 1D vectors. 2D-NDP detects the intrinsic class-relationships between the images by incorporating both class label information and neighborhood information. It can optimally preserve not only the local class information but discriminant information as well. Under the orthogonal constrain, 2D-NDP is developed as orthogonal 2D-NDP for classification. Experiments on the face database and the plant leaf database demonstrate that orthogonal 2D-NDP is effective and feasible for classification.
In this paper, a novel method for predicting RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS) is proposed. In RNATS, two search models, intensification search and diversif...
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In this paper, a novel method for predicting RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS) is proposed. In RNATS, two search models, intensification search and diversification search, are designed to exploit the local regions around the current solution and explore the unvisited space, respectively. Simulation experiments are conducted for six RNA sequences to show that the proposed method is feasible and effective.
In this paper we review the major approaches to nonrigid object reconstruction based on multi-view images. It tries to reflect the profile of this area by focusing more on those subjects that have been given more impo...
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In this paper we review the major approaches to nonrigid object reconstruction based on multi-view images. It tries to reflect the profile of this area by focusing more on those subjects that have been given more importance in the literature. In this context most of the paper is devoted to present all kinds of approaches for non-rigid object reconstruction based on multiview images. A number of references are provided that describe applications of non-rigid object reconstruction based on multiview images The paper ends by addressing some important issues and open questions that can be subject of future research.
Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In t...
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ISBN:
(纸本)9781424471645;9781424471638
Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In the proposed method, each individual component of the protection system in the simulated plane is modeled. Then, the threat report of each component according to the specific tactics is determined based on its real environment. Finally, the comprehensive threat distribution is obtained based on through the D-S evidence theory to combine multi-sources information. The proposed method can easily applied to the evaluation of the effectiveness of the protection system. We make the total threat of the protection system lowest through changes of the protection resources allocation. A numerical example is used to illustrate the efficiency of the proposed method.
In the system of the PV grid-connected generation, because of the dispersion of the PV panel, difference of the sun radiation condition and the shadow of a part of the PV panel, they will cause the serious loss of ene...
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Rough sets,proposed by Pawlak and rough fuzzy sets proposed by Dubois and Prade were expressed with the different computing formulas that were more complex and not conducive to computer operations,In this paper,we use...
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Rough sets,proposed by Pawlak and rough fuzzy sets proposed by Dubois and Prade were expressed with the different computing formulas that were more complex and not conducive to computer operations,In this paper,we use the composition of a fuzzy matrix and fuzzy vectors in a given non-empty finite universal,constitute an algebraic system composed of finite dimensional fuzzy vectors and discuss some properties of the algebraic system about a basis and *** give an effective calculation representation of rough fuzzy sets by the inner and outer products that unify computing of rough sets and rough fuzzy sets with a *** basis of the algebraic system play a key role in this *** give some essential properties of the lower and upper approximation operators generated by reflexive,symmetric,and transitive fuzzy *** reflexive,symmetric,and transitive fuzzy relations are charac terized by the basis of the algebraic system.A set of axioms,as the axiomatic approach,has been constructed to characterize the upper approximation of fuzzy sets on the basis of the algebraic system.
Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising mo...
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Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising models for the physical realization of quantum computers. Despite considerable progress in the past decade, it remains a great challenge to search for new universal resource states with naturally occurring Hamiltonians and to better understand the entanglement structure of these kinds of states. Here we show that most of the resource states currently known can be reduced to the cluster state, the first known universal resource state, via adaptive local measurements at a constant cost. This new quantum state reduction scheme provides simpler proofs of universality of resource states and opens up plenty of space to the search of new resource states.
Inspired by the growth of dendritic trees in biological neurons, we introduce spiking neural P systems with budding rules. By applying these rules in a maximally parallel way, a spiking neural P system can exponential...
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In order to support mobile service of long-distance monitoring and controlling UPS based on Web, a kind of design and implementation solution of embedded UPS (EUPS) system is brought forward in this paper. The design ...
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In view of the problem of motion blurred region segmentation from clear background in still images, a segmenting method based on directional field and fuzzy membership was proposed in this paper. Firstly, motional reg...
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In view of the problem of motion blurred region segmentation from clear background in still images, a segmenting method based on directional field and fuzzy membership was proposed in this paper. Firstly, motional region was located roughly according to the direction obtained from the directional field. Then, blurred region was segmented furthermore based on degree of membership calculated using fuzzy membership function, which was defined to measure the fuzzy degree of image. Finally, motion blurred region was segmented with morphological post processing. The experimental results show that the motion blurred region can be segmented more accurately by proposed method, which can meet the qualification of subsequent retrieving, recognizing and analyzing processing about motional objects.
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