The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, a novel prediction method named VKOPP for electronic system is presented, which utilizes the advantages of Volterra series and OPELM algorithm. Firstly, this algorithm in Volterra series modeling uses the minimum entropy rate method mentioned to simultaneously optimize the embedding dimension and delay time. Secondly, taking advantage of the variable selection and difference calculation...
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...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.