Compare Time Series Mining Approaches for Mapping Function Assessment
To estimate intracranial pressure (ICP) noninvasively, a data mining framework was proposed in our previous work. In the procedure, the mapping function plays an important role to estimate ICP based on the feature vector extracted from arterial blood pressure (ABP) and flow velocity (FV), which is translated to the estimated errors by the mapping function for each entry in the database. In this paper, the different mapping function solutions, linear least squares (LLS), total least squares(TLS) and standard Tikhonov regularization(STR) are systemically tested to compare the possible effects of different solutions on the non-invasive ICP estimation. The conducted comparison demonstrated that the selection of mapping function solution actually influences the estimation. In our previous studies, STR is a better solution for mapping function. Among the tested three solutions for mapping function in this paper, the STR method still shows to be superior to the methods of LLS and TLS.
Shaozhi Wu Peng Xu Yue Wu Marvin Bergsneider Xiao Hu
School of Computer Science and Engineering, University of Electronic Science and Technology of China 2Neural Systems and Dynamics Laboratory, Department of Neurosurgery, the David Geffen School of Medi School of Computer Science and Engineering, University of Electronic Science and Technology of China Neural Systems and Dynamics Laboratory, Department of Neurosurgery, the David Geffen School of Medic
国际会议
2009国际通信电路与系统学术会议(ICCCAS 2009)(2009 International Conference on Communications，Circuits and Systems)
成都
英文
577-580
2009-07-23（万方平台首次上网日期，不代表论文的发表时间）