Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

An interpretable and converging set-membership algorithm

By: Deller, J.R.; Liu, M.S.; Nayeri, M.;

1993 / IEEE / 0-7803-0946-4


This item was taken from the IEEE Periodical ' An interpretable and converging set-membership algorithm ' Set membership (SM)-based techniques, with least square error overlay, suffer from a trade-off between interpretability and proof of convergence. The authors introduce a modified SM algorithm with 'forgetting' covariance updating in conjunction with minimum volume data selecting strategy. The convergence properties of this algorithm and its resemblance to the stochastic approximation method are discussed.<>