Parametric and nonparametric linear mappings of multidimensional data

Mayer Aladjem

doi:10.1016/0031-3203(91)90020-6

Parametric and nonparametric linear mappings of multidimensional data

Mayer Aladjem

Department of Electrical & Computer Engineering

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

17 Scopus citations

Abstract

A new criterion for linear mapping of the samples from two classes is presented. Some parametric and nonparametric forms of the criterion are suggested. Based on them most of the known linear mapping projections can be created. New projections can be obtained as well. An experimental study with synthetic and real data is discussed. It confirms the effectiveness of the new mapping projections for the data with complicated classification structure.

Original language	English
Pages (from-to)	543-553
Number of pages	11
Journal	Pattern Recognition
Volume	24
Issue number	6
DOIs	https://doi.org/10.1016/0031-3203(91)90020-6
State	Published - 1 Jan 1991

Keywords

Classifier design
Exploratory data analysis
Feature extraction
Mapping

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

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10.1016/0031-3203(91)90020-6

Cite this

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abstract = "A new criterion for linear mapping of the samples from two classes is presented. Some parametric and nonparametric forms of the criterion are suggested. Based on them most of the known linear mapping projections can be created. New projections can be obtained as well. An experimental study with synthetic and real data is discussed. It confirms the effectiveness of the new mapping projections for the data with complicated classification structure.",

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N2 - A new criterion for linear mapping of the samples from two classes is presented. Some parametric and nonparametric forms of the criterion are suggested. Based on them most of the known linear mapping projections can be created. New projections can be obtained as well. An experimental study with synthetic and real data is discussed. It confirms the effectiveness of the new mapping projections for the data with complicated classification structure.

AB - A new criterion for linear mapping of the samples from two classes is presented. Some parametric and nonparametric forms of the criterion are suggested. Based on them most of the known linear mapping projections can be created. New projections can be obtained as well. An experimental study with synthetic and real data is discussed. It confirms the effectiveness of the new mapping projections for the data with complicated classification structure.

KW - Classifier design

KW - Exploratory data analysis

KW - Feature extraction

KW - Mapping

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U2 - 10.1016/0031-3203(91)90020-6

DO - 10.1016/0031-3203(91)90020-6

M3 - Article

AN - SCOPUS:0025920368

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SP - 543

EP - 553

JO - Pattern Recognition

JF - Pattern Recognition

IS - 6

ER -

Parametric and nonparametric linear mappings of multidimensional data

Abstract

Keywords

ASJC Scopus subject areas

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