In this article, we consider the existence of trajectory and global attractors for nonclassical diffusion equations with linear fading memory. For this purpose, we will apply the method presented by Chepyzhov and Mira...In this article, we consider the existence of trajectory and global attractors for nonclassical diffusion equations with linear fading memory. For this purpose, we will apply the method presented by Chepyzhov and Miranville [7, 8], in which the authors provide some new ideas in describing the trajectory attractors for evolution equations with memory.展开更多
Global Memory Net (GMNet) is intended to be an effective gateway to the world cultural, historical, and heritage image collections from selected academic educational and research partners in the world. Much of these u...Global Memory Net (GMNet) is intended to be an effective gateway to the world cultural, historical, and heritage image collections from selected academic educational and research partners in the world. Much of these unique collections of great value to education and research are not currently accessible due to distance, form, and technical barriers. This project is to find new ways to enable users to access and exploit these significant research collections via global network. As GMNet is ending its first 5-year phase in October 2005, it has contributed substantially to the community building in digital library development by ac- commodating numerous collaborators and technical staff from various parts of the world to spend 3 to 5 months as a full-member of the GMNet team in Boston. They have come from different parts of China—such as Sichuan, Hainan, Shanghai and Xi’an; Croatia; and Hanoi, Vietnam. In addition to contribute to the overall system development and enhancement of system function- alities, they have brought valuable sample image collections of their own institutions/countries, and actually developed prototype collections as a part of GMNet. This paper describes the exciting and productive experience of the first of this visiting research group in developing the GMNet’s Version 2.0 PHP-based system under Prof. Chen’s overall supervision. It also describes both the system’s technical level structure—user/Web-based application/data, and complex functionalities with multi-collection, multi-lingual, multi-modal searching capabilities; system management capabilities; as well as provisions for user uploads and retrieval for our own projects. This Version 2.0 system is built on the Linux/Apache/PHP/MySQL platform. What is described in this paper is an actual case which has formed a base for further new development by others in the research group. It demonstrates fully the value of the synergistic collaboration among global partners for universal digital library development. More information can b展开更多
In this article, a new descent memory gradient method without restarts is proposed for solving large scale unconstrained optimization problems. The method has the following attractive properties： 1） The search direc...In this article, a new descent memory gradient method without restarts is proposed for solving large scale unconstrained optimization problems. The method has the following attractive properties： 1） The search direction is always a sufficiently descent direction at every iteration without the line search used; 2） The search direction always satisfies the angle property, which is independent of the convexity of the objective function. Under mild conditions, the authors prove that the proposed method has global convergence, and its convergence rate is also investigated. The numerical results show that the new descent memory method is efficient for the given test problems.展开更多
基金supported by NSFC Grant (11031003)the Fundamental Research Funds for the Central Universities+1 种基金support by Fund of excellent young teachers in Shanghai (shgcjs008)Initial Fund of SUES (A-0501-11-016)
文摘In this article, we consider the existence of trajectory and global attractors for nonclassical diffusion equations with linear fading memory. For this purpose, we will apply the method presented by Chepyzhov and Miranville [7, 8], in which the authors provide some new ideas in describing the trajectory attractors for evolution equations with memory.
基金supported by the US National Science Foundation/International Digital Library Program(Grant No.NSF/CISE/IIS-9905833).
文摘Global Memory Net (GMNet) is intended to be an effective gateway to the world cultural, historical, and heritage image collections from selected academic educational and research partners in the world. Much of these unique collections of great value to education and research are not currently accessible due to distance, form, and technical barriers. This project is to find new ways to enable users to access and exploit these significant research collections via global network. As GMNet is ending its first 5-year phase in October 2005, it has contributed substantially to the community building in digital library development by ac- commodating numerous collaborators and technical staff from various parts of the world to spend 3 to 5 months as a full-member of the GMNet team in Boston. They have come from different parts of China—such as Sichuan, Hainan, Shanghai and Xi’an; Croatia; and Hanoi, Vietnam. In addition to contribute to the overall system development and enhancement of system function- alities, they have brought valuable sample image collections of their own institutions/countries, and actually developed prototype collections as a part of GMNet. This paper describes the exciting and productive experience of the first of this visiting research group in developing the GMNet’s Version 2.0 PHP-based system under Prof. Chen’s overall supervision. It also describes both the system’s technical level structure—user/Web-based application/data, and complex functionalities with multi-collection, multi-lingual, multi-modal searching capabilities; system management capabilities; as well as provisions for user uploads and retrieval for our own projects. This Version 2.0 system is built on the Linux/Apache/PHP/MySQL platform. What is described in this paper is an actual case which has formed a base for further new development by others in the research group. It demonstrates fully the value of the synergistic collaboration among global partners for universal digital library development. More information can b
基金supported by the National Science Foundation of China under Grant No.70971076the Foundation of Shandong Provincial Education Department under Grant No.J10LA59
文摘In this article, a new descent memory gradient method without restarts is proposed for solving large scale unconstrained optimization problems. The method has the following attractive properties： 1） The search direction is always a sufficiently descent direction at every iteration without the line search used; 2） The search direction always satisfies the angle property, which is independent of the convexity of the objective function. Under mild conditions, the authors prove that the proposed method has global convergence, and its convergence rate is also investigated. The numerical results show that the new descent memory method is efficient for the given test problems.
