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Order Selection for AR Models by Predictive Least Squares

IP.com Disclosure Number: IPCOM000061857D
Original Publication Date: 1986-Sep-01
Included in the Prior Art Database: 2005-Mar-09

Publishing Venue

IBM

Related People

Authors:
Rissanen, J Wax, M [+details]

Abstract

Disclosed is an algorithm for determining the order of autoregressive (AR) models based on the Predictive Least-Squares principle. The implementation of the order-determining algorithm uses predictive lattice filters, also called ladder forms, that have a modular structure amenable to VLSI implementation. AR models are used in speech modelling and synthesis, equalization of communication channels, spectral estimation, time series analysis and other areas. Given a sequence of t observations of y, we can predict the next observation t+1 of y using a so-called all-pole autoregressive (AR) model of order m as set out in equation (1), (Image Omitted) where the number m and the coefficients a are to be estimated from the t observations of y.