Let g and h be two transcendental entire functions. Suppose that the Fatou set F（goh） contains multiply connected components. In this article, we will consider the growth of the functions g and h.
Security in Ad Hoc network is an important issue under the opening circumstance of application service. Some protocols and models of security auditing have been proposed to ensure rationality of contracting strategy a...Security in Ad Hoc network is an important issue under the opening circumstance of application service. Some protocols and models of security auditing have been proposed to ensure rationality of contracting strategy and operating regulation and used to identify abnormal operation. Model of security auditing based on access control of devices will be advanced to register sign of devices and property of event of access control and to audit those actions. In the end, the model is analyzed and simulated.展开更多
Suppose that f(z) is a transcendental entire function and that F(f) contains unbounded Fatou components. In this article, we obtained some links between the lower bounds of the lower order of f and the angle of an ang...Suppose that f(z) is a transcendental entire function and that F(f) contains unbounded Fatou components. In this article, we obtained some links between the lower bounds of the lower order of f and the angle of an angular sector which is completely contained in an unbounded Fatou component of F(f). Then, we investigate the bounded components for the Julia set J(f) of a transcendental entire function f(z) and obtain a sufficient and necessary condition.展开更多
In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform （SIFT）, and inherits t...In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform （SIFT）, and inherits the spirit of the spatial pyramid matching model （SPM）. In a flexible way of partitioning the original texture images, our approach can produce sufficient informative local features and thereby form a reliable feature pond or train a new class-specific dictionary. To take full advantage of this feature pond, we develop a group-collaboratively representation-based strategy （GCRS） for the final classification. It is solved by the well-known group lasso. But we go beyond of this and propose a locality-constraint method to speed up this, named local constraint-GCRS （LC-GCRS）. Experimental results on three public texture datasets demonstrate the proposed approach achieves competitive outcomes and even outperforms the state-of-the-art methods. Particularly, most of methods cannot work well when only a few samples of each category are available for training, but our approach still achieves very high classification accuracy, e.g. an average accuracy of 92.1% for the Brodatz dataset when only one image is used for training, significantly higher than any other methods.展开更多
In practical applications, we often have to deal with high-order data, for example, a grayscale image and a video clip are intrinsically a 2nd-order tensor and a 3rd-order tensor, respectively. In order to satisty the...In practical applications, we often have to deal with high-order data, for example, a grayscale image and a video clip are intrinsically a 2nd-order tensor and a 3rd-order tensor, respectively. In order to satisty these high-order data, it is conventional to vectorize these data in advance, which often destroys the intrinsic structures of the data and includes the curse of dimensionality. For this reason, we consider the problem of high-order data representation and classification, and propose a tensor based fisher discriminant analysis （FDA）, which is a generalized version of FDA, named as GFDA. Experimental results show our GFDA outperforms the existing methods, such as the 2-directional 2-dimensional principal component analysis （（2D）2pCA）, 2-directional 2-dimensional linear discriminant analysis （（2D）2LDA）, and multilinear discriminant analysis （MDA）, in high-order data classification under a lower compression ratio.展开更多
Chunk alignment for the bilingual corpus is the base of Example-based Machine Translation. An anchor-based English-Chinese bilingual chunk alignment model and the corresponding algorithm of alignment are presented in ...Chunk alignment for the bilingual corpus is the base of Example-based Machine Translation. An anchor-based English-Chinese bilingual chunk alignment model and the corresponding algorithm of alignment are presented in this paper. It can effectively overcome the sparse data problem due to the limited size of the bilingual corpus. In this model, the chunk segmentation disambiguation is delayed to the alignment process, and hence the accuracy of chunk segmentation is improved. The experimental results demonstrate the feasibility and viability of this model.展开更多
文摘Let g and h be two transcendental entire functions. Suppose that the Fatou set F（goh） contains multiply connected components. In this article, we will consider the growth of the functions g and h.
文摘Security in Ad Hoc network is an important issue under the opening circumstance of application service. Some protocols and models of security auditing have been proposed to ensure rationality of contracting strategy and operating regulation and used to identify abnormal operation. Model of security auditing based on access control of devices will be advanced to register sign of devices and property of event of access control and to audit those actions. In the end, the model is analyzed and simulated.
文摘Suppose that f(z) is a transcendental entire function and that F(f) contains unbounded Fatou components. In this article, we obtained some links between the lower bounds of the lower order of f and the angle of an angular sector which is completely contained in an unbounded Fatou component of F(f). Then, we investigate the bounded components for the Julia set J(f) of a transcendental entire function f(z) and obtain a sufficient and necessary condition.
文摘In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform （SIFT）, and inherits the spirit of the spatial pyramid matching model （SPM）. In a flexible way of partitioning the original texture images, our approach can produce sufficient informative local features and thereby form a reliable feature pond or train a new class-specific dictionary. To take full advantage of this feature pond, we develop a group-collaboratively representation-based strategy （GCRS） for the final classification. It is solved by the well-known group lasso. But we go beyond of this and propose a locality-constraint method to speed up this, named local constraint-GCRS （LC-GCRS）. Experimental results on three public texture datasets demonstrate the proposed approach achieves competitive outcomes and even outperforms the state-of-the-art methods. Particularly, most of methods cannot work well when only a few samples of each category are available for training, but our approach still achieves very high classification accuracy, e.g. an average accuracy of 92.1% for the Brodatz dataset when only one image is used for training, significantly higher than any other methods.
文摘In practical applications, we often have to deal with high-order data, for example, a grayscale image and a video clip are intrinsically a 2nd-order tensor and a 3rd-order tensor, respectively. In order to satisty these high-order data, it is conventional to vectorize these data in advance, which often destroys the intrinsic structures of the data and includes the curse of dimensionality. For this reason, we consider the problem of high-order data representation and classification, and propose a tensor based fisher discriminant analysis （FDA）, which is a generalized version of FDA, named as GFDA. Experimental results show our GFDA outperforms the existing methods, such as the 2-directional 2-dimensional principal component analysis （（2D）2pCA）, 2-directional 2-dimensional linear discriminant analysis （（2D）2LDA）, and multilinear discriminant analysis （MDA）, in high-order data classification under a lower compression ratio.
文摘Chunk alignment for the bilingual corpus is the base of Example-based Machine Translation. An anchor-based English-Chinese bilingual chunk alignment model and the corresponding algorithm of alignment are presented in this paper. It can effectively overcome the sparse data problem due to the limited size of the bilingual corpus. In this model, the chunk segmentation disambiguation is delayed to the alignment process, and hence the accuracy of chunk segmentation is improved. The experimental results demonstrate the feasibility and viability of this model.
