IEICE Trans - 2-D Adaptive Autoregressive Modeling Using New Lattice Structure

2-D Adaptive Autoregressive Modeling Using New Lattice Structure

Takayuki NAKACHI  Katsumi YAMASHITA  Nozomu HAMADA

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E79-A   No.8   pp.1145-1150
Publication Date: 1996/08/25
Online ISSN:
DOI:
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
Category:
Keyword:
lattice filter,  2-D signal processing,  adaptive filter,  linear prediction,  AR modeling,

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Summary:
The present paper investigates a two-dimensional (2-D) adaptive lattice filter used for modeling 2-D AR fields. The 2-D least mean square (LMS) lattice algorithm is used to update the filter coefficients. The proposed adaptive lattice filter can represent a wider class of 2-D AR fields than previous ones. Furthremore, its structure is also shown to possess orthogonality in the backward prediction error fields. These result in superior convergence and tracking properties to the adaptive transversal filter and other adaptive 2-D lattice models. Then, the convergence property of the proposed adaptive LMS lattice algorithm is discussed. The effectiveness of the proposed model is evaluated for parameter identification through computer simulation.