The Application of Artificial Neural Networks to Stellar Classification

Coryn A. L. Jones; Mike Irwin; Ted von Hippel

The Application of Artificial Neural Networks to Stellar Classification

Coryn A. L. Jones, Mike Irwin, Ted von Hippel

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

Abstract

We are working on a project to automate the multi-parameter classification of stellar spectra using Principal Components Analysis (PCA) and Artificial Neural Networks. We present here the usefulness of PCA as a form of spectral data compression, and our results to date of classification on the MK system.

Original language	American English
Journal	Astronomical Data Analysis Software and Systems V
Volume	101
State	Published - Jan 1 1996
Externally published	Yes

Keywords

stellar classification automation

Disciplines

Instrumentation

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The Application of Artificial Neural Networks to Stellar ClassifiFinal published version, 388 KBLicense: CC BY

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title = "The Application of Artificial Neural Networks to Stellar Classification",

abstract = " We are working on a project to automate the multi-parameter classification of stellar spectra using Principal Components Analysis (PCA) and Artificial Neural Networks. We present here the usefulness of PCA as a form of spectral data compression, and our results to date of classification on the MK system.",

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language = "American English",

volume = "101",

journal = "Astronomical Data Analysis Software and Systems V",

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T1 - The Application of Artificial Neural Networks to Stellar Classification

AU - Jones, Coryn A. L.

AU - Irwin, Mike

AU - Hippel, Ted von

PY - 1996/1/1

Y1 - 1996/1/1

N2 - We are working on a project to automate the multi-parameter classification of stellar spectra using Principal Components Analysis (PCA) and Artificial Neural Networks. We present here the usefulness of PCA as a form of spectral data compression, and our results to date of classification on the MK system.

AB - We are working on a project to automate the multi-parameter classification of stellar spectra using Principal Components Analysis (PCA) and Artificial Neural Networks. We present here the usefulness of PCA as a form of spectral data compression, and our results to date of classification on the MK system.

KW - stellar classification automation

UR - https://commons.erau.edu/publication/2073

M3 - Article

VL - 101

JO - Astronomical Data Analysis Software and Systems V

JF - Astronomical Data Analysis Software and Systems V

ER -

The Application of Artificial Neural Networks to Stellar Classification

Abstract

Keywords

Disciplines

Access to Document

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