Parameter estimation for two-dimensional vector models using neural networks
Date
1995
Authors
Xu, Lin, author
Azimi-Sadjadi, Mahmood R., author
IEEE, publisher
Journal Title
Journal ISSN
Volume Title
Abstract
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.
Description
Rights Access
Subject
parameter estimation
autoregressive processes
convergence of numerical methods
image processing
learning (artificial intelligence)
least squares approximations
neural nets
vectors