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Parameter estimation for two-dimensional vector models using neural networks

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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 )

Date of Publication:

Dec 1995

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