Modified extended kalman filtering for supervised learning

Guanrong Chen; Haluk ÖGˇmen

doi:10.1080/00207729308949553

Modified extended kalman filtering for supervised learning

Guanrong Chen
, Haluk ÖGˇmen

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

9 Citations (Scopus)

Abstract

We apply the modified extended Kalman filter to develop a learning algorithm for feedforward networks. The resulting algorithm improves the existing extended Kalman filter based scheme in both speed of convergence and accuracy of estimation. © 1993 Taylor & Francis Group, LLC.

Original language	English
Pages (from-to)	1207-1214
Journal	International Journal of Systems Science
Volume	24
Issue number	6
DOIs	https://doi.org/10.1080/00207729308949553
Publication status	Published - Jun 1993
Externally published	Yes

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title = "Modified extended kalman filtering for supervised learning",

abstract = "We apply the modified extended Kalman filter to develop a learning algorithm for feedforward networks. The resulting algorithm improves the existing extended Kalman filter based scheme in both speed of convergence and accuracy of estimation. {\textcopyright} 1993 Taylor \& Francis Group, LLC.",

author = "Guanrong Chen and Haluk {\"O}Gˇmen",

year = "1993",

month = jun,

doi = "10.1080/00207729308949553",

language = "English",

volume = "24",

pages = "1207--1214",

journal = "International Journal of Systems Science",

issn = "0020-7721",

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T1 - Modified extended kalman filtering for supervised learning

AU - Chen, Guanrong

AU - ÖGˇmen, Haluk

PY - 1993/6

Y1 - 1993/6

N2 - We apply the modified extended Kalman filter to develop a learning algorithm for feedforward networks. The resulting algorithm improves the existing extended Kalman filter based scheme in both speed of convergence and accuracy of estimation. © 1993 Taylor & Francis Group, LLC.

AB - We apply the modified extended Kalman filter to develop a learning algorithm for feedforward networks. The resulting algorithm improves the existing extended Kalman filter based scheme in both speed of convergence and accuracy of estimation. © 1993 Taylor & Francis Group, LLC.

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UR - https://www.scopus.com/pages/publications/0000387707#tab=impact

U2 - 10.1080/00207729308949553

DO - 10.1080/00207729308949553

M3 - RGC 21 - Publication in refereed journal

SN - 0020-7721

VL - 24

SP - 1207

EP - 1214

JO - International Journal of Systems Science

JF - International Journal of Systems Science

IS - 6

ER -

Modified extended kalman filtering for supervised learning

Abstract

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