By Topic

Parameter estimation for two-dimensional vector models using neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Lin Xu ; Eastman Kodak Co., Billerica, MA, USA ; Azimi-Sadjadi, M.R.

This correspondence addresses the problem of two-dimensional (2-D) vector image model parameter estimation using a new recursive least squares (RLS)-based learning method. Vector autoregressive (AR) models with various 1-D and 2-D, causal and noncausal regions of support (ROS) are considered. Numerical results are presented which demonstrate the usefulness of the proposed scheme for on-line implementation

Published in:

Signal Processing, IEEE Transactions on  (Volume:43 ,  Issue: 12 )