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Orthogonal feature selection method. [For preprocessing of man spectral data]

Abstract

A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)
Authors:
Kowalski, B R; [1]  Bender, C F
  1. Univ. of Washington, Seattle
Publication Date:
Jan 01, 1976
Product Type:
Journal Article
Reference Number:
ERA-02-001133; EDB-76-087418
Resource Relation:
Journal Name: Pattern Recognition; (United Kingdom); Journal Volume: 8
Subject:
37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; MASS SPECTROSCOPY; DATA PROCESSING; MOLECULAR STRUCTURE; PROCESSING; SPECTROSCOPY; 400104* - Spectral Procedures- (-1987)
OSTI ID:
7156749
Country of Origin:
United Kingdom
Language:
English
Other Identifying Numbers:
Journal ID: CODEN: PTNRA
Submitting Site:
TIC
Size:
Pages: 1-4
Announcement Date:
Oct 01, 1976

Citation Formats

Kowalski, B R, and Bender, C F. Orthogonal feature selection method. [For preprocessing of man spectral data]. United Kingdom: N. p., 1976. Web. doi:10.1016/0031-3203(76)90023-6.
Kowalski, B R, & Bender, C F. Orthogonal feature selection method. [For preprocessing of man spectral data]. United Kingdom. https://doi.org/10.1016/0031-3203(76)90023-6
Kowalski, B R, and Bender, C F. 1976. "Orthogonal feature selection method. [For preprocessing of man spectral data]." United Kingdom. https://doi.org/10.1016/0031-3203(76)90023-6.
@misc{etde_7156749,
title = {Orthogonal feature selection method. [For preprocessing of man spectral data]}
author = {Kowalski, B R, and Bender, C F}
abstractNote = {A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)}
doi = {10.1016/0031-3203(76)90023-6}
journal = []
volume = {8}
journal type = {AC}
place = {United Kingdom}
year = {1976}
month = {Jan}
}