Skip to main content
Extensions of Dynamic Programming, Machine Learning, Discrete Optimization
Extensions of Dynamic Programming, Machine Learning, Discrete Optimization
Main navigation
Home
People
All Profiles
Principal Investigators
Postdoctoral Fellows
Students
Alumni
Former Members
Events
All Events
Events Calendar
News
Teaching
Collaborators
Books
Contact Us
transient analysis
Transient analysis of data-normalized adaptive filters
1 min read ·
Tue, Aug 6 2019
News
transient analysis
filters
ISL Highlighted Publications
T. Y. Al-Naffouri and A. H. Sayed, "Transient analysis of data-normalized adaptive filters", IEEE Transactions on Signal Processing. vol. 51 , pp. 639-652, Mar 2003. Abstract: This paper develops an approach to the transient analysis of adaptive filters with data normalization. Among other results, the derivation characterizes the transient behavior of such filters in terms of a linear time-invariant state-space model. The stability, of the model then translates into the mean-square stability of the adaptive filters. Likewise, the steady-state operation of the model provides information about
