机构

• 沈阳自动化研究所 [2]
• 长春光学精密机械与物... [1]
• 上海技术物理研究所 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [3]
• 会议论文 [2]

发表日期

• 2021 [2]
• 2019 [1]
• 2014 [1]
• 2009 [1]

学科主题

筛选

浏览/检索结果: 共5条，第1-5条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Research on Intrusion Detection of Industrial Control System Based on FastICA-SVM Method 会议论文  OAI收割 Dublin, Ireland, July 19-23, 2021 作者:  Chen, Haonan;  Liu XD(刘贤达);  Wang TY(王天宇);  Zhang, Xuejing   |  收藏  |  浏览/下载：28/0  |  提交时间：2021/08/21 Intrusion detection  FastICA  SVM   基于VMD和改进的FastICA算法的旋转机械故障信号分离方法研究 期刊论文  OAI收割 仪器仪表标准化与计量, 2021, 期号: 1, 页码: 15-19 作者:  孙懿;  刘意杨;  宋纯贺;  冯铁英;  张雪健   |  收藏  |  浏览/下载：37/0  |  提交时间：2021/03/14 旋转机械  故障诊断  VMD FastICA算法  源信号   Research on Applications of FastICA Algorithm in the Detection of Dangerous Liquids 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2019, 卷号: 33, 期号: 2 作者:  Zhou, Dongmei;  Qiu, Shi;  Tan, Jiahai;  Li, Xiaofeng;  Chen, Chen   |  收藏  |  浏览/下载：53/0  |  提交时间：2018/11/21 Self-adaption  Uwb Centimeter Wave  Fastica  S-parameter  Detection Of Dangerous Liquids   Using Improved ICA Method for Hyperspectral Data Classification 期刊论文  OAI收割 Arabian Journal for Science and Engineering, 2014, 卷号: 39, 期号: 1, 页码: 181-189 - 收藏  |  浏览/下载：16/0  |  提交时间：2016/05/16 Remote sensing  Hyperspectral data  Classification  Independent component analysis (ICA)  Support vector machine (SVM)  FastICA   Infrared face recognition using linear subspace analysis (EI CONFERENCE) 会议论文  OAI收割 MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral Image Processing and Pattern Recognition, October 30, 2009 - November 1, 2009, Yichang, China 作者:  Wang D. 收藏  |  浏览/下载：34/0  |  提交时间：2013/03/25 Infrared image offers the main advantage over visible image of being invariant to illumination changes for face recognition. In this paper  based on the introduction of main methods of linear subspace analysis  such as Principal Component Analysis (PCA)  Linear Discriminant Analysis(LDA) and Fast Independent Component Analysis (FastICA)  the application of these methods to the recognition of infrared face images offered by OTCBVS workshop are investigated  and the advantages and disadvantages are compared. Experimental results show that the combination approach of PCA and LDA leads to better classification performance than single PCA approach or LDA approach  while the FastICA approach leads to the best classification performance with the improvement of nearly 5% compared with the combination approach. 2009 Copyright SPIE - The International Society for Optical Engineering.