We discuss the technical rationale,challenges,and potential for achieving “optics-to-the chip” via the intimate integration of photonics components such as lasers,detectors,and modulators with VLSI electronics.We re...We discuss the technical rationale,challenges,and potential for achieving “optics-to-the chip” via the intimate integration of photonics components such as lasers,detectors,and modulators with VLSI electronics.We review the progress made towards commercializing this technology for high-density optical transceivers and switching products.展开更多
Sun Microsystems公司1999年1月25日推出了具有革命性的新技术Jini,将Java技术所建立起来的基于开放性标准的以网络为中心的计算模式向前推进。Jini技术摧毁了传统的网络壁垒,它能使用户从任何地点将任何消费类电子产品和企业设备简单...Sun Microsystems公司1999年1月25日推出了具有革命性的新技术Jini,将Java技术所建立起来的基于开放性标准的以网络为中心的计算模式向前推进。Jini技术摧毁了传统的网络壁垒,它能使用户从任何地点将任何消费类电子产品和企业设备简单地与网络相连。Jini技术的重要性就是简单,有了这个“简单性”,就完全不必考虑过去那些兼容性、可靠性或是管理性能等诸多问题,正是这些传统的壁垒限制了人们在网络之间实现成功的配置。展开更多
One of the most general data compression and purpose feature extraction technique isprincipal component analysis （PCA）. There has been much interest recently on PCA forengineers. Assum that X is an n-dimensional inp...One of the most general data compression and purpose feature extraction technique isprincipal component analysis （PCA）. There has been much interest recently on PCA forengineers. Assum that X is an n-dimensional input data vector that has been centered to zeromean. The purpose of the PCA is to find those p （p≤n） linear combinations w<sub>1</sub><sup>T</sup>x,..., w<sub>P</sub><sup>T</sup>展开更多
文摘We discuss the technical rationale,challenges,and potential for achieving “optics-to-the chip” via the intimate integration of photonics components such as lasers,detectors,and modulators with VLSI electronics.We review the progress made towards commercializing this technology for high-density optical transceivers and switching products.
基金Project supported in part by the Doctral Program of the State Education Commission of ChinaShanghai Natural Science Foundations.
文摘One of the most general data compression and purpose feature extraction technique isprincipal component analysis （PCA）. There has been much interest recently on PCA forengineers. Assum that X is an n-dimensional input data vector that has been centered to zeromean. The purpose of the PCA is to find those p （p≤n） linear combinations w<sub>1</sub><sup>T</sup>x,..., w<sub>P</sub><sup>T</sup>
