In this paper, an improved gradient iterative （GI） algorithm for solving the Lyapunov matrix equations is studied. Convergence of the improved method for any initial value is proved with some conditions. Compared wi...In this paper, an improved gradient iterative （GI） algorithm for solving the Lyapunov matrix equations is studied. Convergence of the improved method for any initial value is proved with some conditions. Compared with the GI algorithm, the improved algorithm reduces computational cost and storage. Finally, the algorithm is tested with GI several numerical examples.展开更多
By the transformation relations between complementary judgement matrix and recip- rocal judgement matrix,this paper proposes two methods for improving the consistency of com- plementary judgement matrix and gives tw...By the transformation relations between complementary judgement matrix and recip- rocal judgement matrix,this paper proposes two methods for improving the consistency of com- plementary judgement matrix and gives two simple practical iterative algorithms.These two al- gorithms are easy to implementon computer,and the modified complementary judgementmatri- ces remain most information that original matrix contains.Thus the methods supplement and develop the theory and methodology for improving consistency of complementary judgement matrix展开更多
It is very important to accurately recognize and locate pulverized and block coal seen in a coal mine's infrared image monitoring system. Infrared monitor images of pulverized and block coal were sampled in the ro...It is very important to accurately recognize and locate pulverized and block coal seen in a coal mine's infrared image monitoring system. Infrared monitor images of pulverized and block coal were sampled in the roadway of a coal mine. Texture statistics from the grey level dependence matrix were selected as the criterion for classification. The distributions of the texture statistics were calculated and analysed. A normalizing function was added to the front end of the BP network with one hidden layer. An additional classification layer is joined behind the linear layer. The recognition of pulverized from block coal images was tested using the improved BP network. The results of the experiment show that texture variables from the grey level dependence matrix can act as recognizable features of the image. The innovative improved BP network can then recognize the pulverized and block coal images.展开更多
Matrix attachment regions or matrix associated regions (MARs) were special DNA sequences in chromatin of eukaryotic cells that tightly associated with the nuclear matrix or scaffold in vitro after a combination of nuc...Matrix attachment regions or matrix associated regions (MARs) were special DNA sequences in chromatin of eukaryotic cells that tightly associated with the nuclear matrix or scaffold in vitro after a combination of nuclease digestion and extraction. They were also called scaffold attachment regions(SARs) . It was found that MARs could improve the expression level and the stability of foreign genes in transgenic plants. The reason might be that a transgene flanked by MARs was transmitted into the plant cells, the MARs would attach the nuclear展开更多
基金Project supported by the National Natural Science Foundation of China （Grant No.10271074）, and the Special Funds for Major Specialities of Shanghai Education Commission （Grant No.J50101）
文摘In this paper, an improved gradient iterative （GI） algorithm for solving the Lyapunov matrix equations is studied. Convergence of the improved method for any initial value is proved with some conditions. Compared with the GI algorithm, the improved algorithm reduces computational cost and storage. Finally, the algorithm is tested with GI several numerical examples.
基金Supported by the National Natural Science Foundation of China(79970 0 93 ) and the Subject of PLAUniversity of Science and Technology
文摘By the transformation relations between complementary judgement matrix and recip- rocal judgement matrix,this paper proposes two methods for improving the consistency of com- plementary judgement matrix and gives two simple practical iterative algorithms.These two al- gorithms are easy to implementon computer,and the modified complementary judgementmatri- ces remain most information that original matrix contains.Thus the methods supplement and develop the theory and methodology for improving consistency of complementary judgement matrix
基金Project 20050290010 supported by the Doctoral Foundation of Chinese Education Ministry
文摘It is very important to accurately recognize and locate pulverized and block coal seen in a coal mine's infrared image monitoring system. Infrared monitor images of pulverized and block coal were sampled in the roadway of a coal mine. Texture statistics from the grey level dependence matrix were selected as the criterion for classification. The distributions of the texture statistics were calculated and analysed. A normalizing function was added to the front end of the BP network with one hidden layer. An additional classification layer is joined behind the linear layer. The recognition of pulverized from block coal images was tested using the improved BP network. The results of the experiment show that texture variables from the grey level dependence matrix can act as recognizable features of the image. The innovative improved BP network can then recognize the pulverized and block coal images.
文摘Matrix attachment regions or matrix associated regions (MARs) were special DNA sequences in chromatin of eukaryotic cells that tightly associated with the nuclear matrix or scaffold in vitro after a combination of nuclease digestion and extraction. They were also called scaffold attachment regions(SARs) . It was found that MARs could improve the expression level and the stability of foreign genes in transgenic plants. The reason might be that a transgene flanked by MARs was transmitted into the plant cells, the MARs would attach the nuclear
