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自动化与信息科学期刊
SJR: 0.238 SNIP: 0.464 CiteScore™: 0.27

ISSN 打印: 1064-2315
ISSN 在线: 2163-9337

卷:
卷 51, 2019 卷 50, 2018 卷 49, 2017 卷 48, 2016 卷 47, 2015 卷 46, 2014 卷 45, 2013 卷 44, 2012 卷 43, 2011 卷 42, 2010 卷 41, 2009 卷 40, 2008 卷 39, 2007 卷 38, 2006 卷 37, 2005 卷 36, 2004 卷 35, 2003 卷 34, 2002 卷 33, 2001 卷 32, 2000 卷 31, 1999 卷 30, 1998 卷 29, 1997 卷 28, 1996

自动化与信息科学期刊

DOI: 10.1615/JAutomatInfScien.v41.i5.50
pages 41-51

Asymptotics of Linear Recurrent Regression under Diffuse Initialization

Boris A. Skorohod
Sevastopol National Technical University, Ukraine

ABSTRACT

The behavior of recurrent least squares method in the absence of a priori information with respect to estimated unknown parameters is studied. The developed approach allows one to present its characteristics in analytical form, to explain the divergence phenomenon and to suggest a limiting recurrent estimation algorithm independent of a large parameter characterizing initial uncertainty and leading to divergence.


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