视频监控是目前安防产业中最重要的一部分,网络视频监控由于其易管理、易扩展、可远程监控等优势,已经成为发展的大趋势。但由于传统以太网100米传输距离的限制,网络视频监控系统的监控距离受到了很大的限制。本文主要介绍如何通过 LRE(...视频监控是目前安防产业中最重要的一部分,网络视频监控由于其易管理、易扩展、可远程监控等优势,已经成为发展的大趋势。但由于传统以太网100米传输距离的限制,网络视频监控系统的监控距离受到了很大的限制。本文主要介绍如何通过 LRE(Long Range Ethernet)物理层芯片如何使10M以太网在普通网线上的传输距离达到一千米以上,并比较了这种应用相对现有解决方案的优势。展开更多
Incomplete data samples have a serious impact on the effectiveness of data mining.Aiming at the LRE historical test samples,based on correlation analysis of condition parameter,this paper introduced principle componen...Incomplete data samples have a serious impact on the effectiveness of data mining.Aiming at the LRE historical test samples,based on correlation analysis of condition parameter,this paper introduced principle component analysis(PCA)and proposed a complete analysis method based on PCA for incomplete samples.At first,the covariance matrix of complete data set was calculated;Then,according to corresponding eigenvalues which were in descending,a principle matrix composed of eigen-vectors of covariance matrix was made;Finally,the vacant data was estimated based on the principle matrix and the known data.Compared with traditional method validated the method proposed in this paper has a better effect on complete test samples.An application example shows that the method suggested in this paper can update the value in use of historical test data.展开更多
文摘视频监控是目前安防产业中最重要的一部分,网络视频监控由于其易管理、易扩展、可远程监控等优势,已经成为发展的大趋势。但由于传统以太网100米传输距离的限制,网络视频监控系统的监控距离受到了很大的限制。本文主要介绍如何通过 LRE(Long Range Ethernet)物理层芯片如何使10M以太网在普通网线上的传输距离达到一千米以上,并比较了这种应用相对现有解决方案的优势。
基金supported by National Natural Science Foundation of China(No.51075391)
文摘Incomplete data samples have a serious impact on the effectiveness of data mining.Aiming at the LRE historical test samples,based on correlation analysis of condition parameter,this paper introduced principle component analysis(PCA)and proposed a complete analysis method based on PCA for incomplete samples.At first,the covariance matrix of complete data set was calculated;Then,according to corresponding eigenvalues which were in descending,a principle matrix composed of eigen-vectors of covariance matrix was made;Finally,the vacant data was estimated based on the principle matrix and the known data.Compared with traditional method validated the method proposed in this paper has a better effect on complete test samples.An application example shows that the method suggested in this paper can update the value in use of historical test data.
