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	On-Line Fault Protection for ReRAM-Based Neural Networks 期刊论文 OAI收割 IEEE TRANSACTIONS ON COMPUTERS, 2023, 卷号: 72, 期号: 2, 页码: 423-437 作者: Li, Wen; Wang, Ying; Liu, Cheng; He, Yintao; Liu, Lian \| 收藏 \| 浏览/下载：13/0 \| 提交时间：2023/07/12 Training Fault detection Computational modeling Image edge detection Memristors Neural networks Kernel Deep neural network hard fault ReRAM reliability soft fault
	Application of quantitative fault tree analysis based on fuzzy synthetic evaluation to software development for space camera (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011, August 8, 2011 - August 10, 2011, Zhengzhou, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 Software reliability analysis is a significant measure to guide design of software reliability. Now software fault tree method to carry on software reliability analysis is used more and more. But it can only qualitative carry on the analysis because of many reasons. For example the scale of software is enlarging the software architecture is getting more and more complex the reason of software fault is very difficult to analyze the software is difference with hardware and it is very hard to obtain the expiration the quantitative data and so on. The space camera is extremely high to the reliable request. So the qualitative analysis is unable to satisfy the analysis request. In view of space camera characteristics a method of fault tree analysis based on fuzzy synthetic evaluation is proposed. The results show that the new method makes software quantitative fault tree analysis possible and optimizes. It can also solve the problem of software component which is unable to quantize precisely. 2011 IEEE.
	Application of Vague set to Software rating ascertainment for space camera (EI CONFERENCE) 会议论文 OAI收割 2nd International Conference on Information Science and Engineering, ICISE2010, December 4, 2010 - December 6, 2010, Hangzhou, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 Software rating ascertainment is very important in development of space camera software system. It can guide the software measurement and management and help designer improve system reliability finally. Fault Tree Analysis is a common method to analyze the danger reason and fix on bottom events. The most significant step is calculating the occurrence probabilistic of top event namely the occurrence probabilistic of dangerous event. Because software failure cause is anfractuous and available data are hard to get a modeling method for bottom event is proposed based on Vague set to calculate the occurrence probabilistic of top event. Experimental results show that the new approach of Vague set can guide the Software rating ascertainment which is ascertained using qualitative analysis. The results also show that the new method makes software rating ascertainment have the quantificational evidence. 2010 IEEE.