Abstract
We propose a principal component analysis algorithm based on our previous work and analyze its deterministic discrete-time (DDT) system. We prove that its DDT system is always bounded for the small constant learning gain and can almost always deliver a principal component. The difference between Oja's algorithm and our proposed algorithm cannot be observed from their corresponding deterministic continuous-time systems.
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.
