A Novel Weighed Hidden Markov Autoregressive Approach for Trend Prediction of Electronic Systems

摘要：

In this paper,a novel condition trend prediction method named WHMAR for electronic systems is presented,which is based on weighed Hidden Markov model (HMM) and autoregressive model(AR). The basic idea is constructing AR prediction cells as the output of HMM,which leads to a segmentation of the time series into different AR models. The hidden state sequence of the Markov chain is chosen and predicted firstly by means of weighed method.In a second step,the output results of this model are computed by the AR model as the prediction output. The method is tested on the trend prediction of complex chaotic time series and typical electronic equipments BIT states,and the experiment results are promising.

关键词： trendprediction electronic system.Hidden Markov model autoregressive model trend prediction.

作者: Liu Zhen Huang Jianguo Wang Houjun Luo Xin

作者单位: School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 61 School of Communication and Information Engineering,University of Electronic Science and Technology

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 182-186

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）