Abstract
In this study we have used recurrence analysis (RA) to classify ERPs that appear from episodic memory retrieval in old/new recognition task. Since RA is based on embedding phase space, we have used correlation dimension and autocorrelation function in order to estimate embedding dimension and the lag time between successive components of each of embedding space vectors alternatively. According to RA the rates of classification have been improved in comparison to previous study. We have obtained 98.9% accuracy for train data and 97.7% for test data. Furthermore we could classify ERPs with line interference noise using RA.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
