Abstract
In practical applications especially in biomedical signal processing, a large number of sensors is available but only one or a very few are desired. The simultaneous blind source separation (BSS) technique always introduces large computational load. A contrast function is formulated associated with normalized kurtosis. Furthermore, an improved learning algorithm is derived based on the standard gradient descent rule. In contrast to simultaneous BSS, the proposed method can provide more flexibility and has some potential advantages in terms of computational load. Computer simulations illustrate its performance.
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 callMore From: DEStech Transactions on Engineering and Technology Research
Disclaimer: 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.
