A note on exact correspondences between adaptive learning algorithms and the Kalman filter

Michele Berardi; Jaqueson K. Galimberti

doi:10.1016/j.econlet.2012.10.002

A note on exact correspondences between adaptive learning algorithms and the Kalman filter

Michele Berardi, Jaqueson K. Galimberti

Economics

Research output: Contribution to journal › Article › peer-review

Abstract

We extend the correspondences between adaptive learning algorithms and the Kalman filter to formulations with time-varying gains. Our correspondences hold exactly, in a computational implementation sense, and we discuss how they relate to previous approximate correspondences found in the literature. © 2012 Elsevier B.V.

Original language	English
Pages (from-to)	139-142
Number of pages	3
Journal	Economics Letters
Volume	118
Issue number	1
DOIs	https://doi.org/10.1016/j.econlet.2012.10.002
Publication status	Published - Jan 2013

Keywords

Adaptive learning
Kalman filter
Least squares
Stochastic gradient

Access to Document

10.1016/j.econlet.2012.10.002

Cite this

@article{8532087d26fd4e1989c2868453df86ee,

title = "A note on exact correspondences between adaptive learning algorithms and the Kalman filter",

abstract = "We extend the correspondences between adaptive learning algorithms and the Kalman filter to formulations with time-varying gains. Our correspondences hold exactly, in a computational implementation sense, and we discuss how they relate to previous approximate correspondences found in the literature. {\textcopyright} 2012 Elsevier B.V.",

keywords = "Adaptive learning, Kalman filter, Least squares, Stochastic gradient",

author = "Michele Berardi and Galimberti, {Jaqueson K.}",

year = "2013",

month = jan,

doi = "10.1016/j.econlet.2012.10.002",

language = "English",

volume = "118",

pages = "139--142",

journal = "Economics Letters",

issn = "0165-1765",

publisher = "Elsevier BV",

number = "1",

}

TY - JOUR

T1 - A note on exact correspondences between adaptive learning algorithms and the Kalman filter

AU - Berardi, Michele

AU - Galimberti, Jaqueson K.

PY - 2013/1

Y1 - 2013/1

N2 - We extend the correspondences between adaptive learning algorithms and the Kalman filter to formulations with time-varying gains. Our correspondences hold exactly, in a computational implementation sense, and we discuss how they relate to previous approximate correspondences found in the literature. © 2012 Elsevier B.V.

AB - We extend the correspondences between adaptive learning algorithms and the Kalman filter to formulations with time-varying gains. Our correspondences hold exactly, in a computational implementation sense, and we discuss how they relate to previous approximate correspondences found in the literature. © 2012 Elsevier B.V.

KW - Adaptive learning

KW - Kalman filter

KW - Least squares

KW - Stochastic gradient

U2 - 10.1016/j.econlet.2012.10.002

DO - 10.1016/j.econlet.2012.10.002

M3 - Article

SN - 0165-1765

VL - 118

SP - 139

EP - 142

JO - Economics Letters

JF - Economics Letters

IS - 1

ER -

A note on exact correspondences between adaptive learning algorithms and the Kalman filter

Abstract

Keywords

Access to Document

Fingerprint

Cite this