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Authors: Youness Aliyari Ghassabeh and Hamid Abrishami Moghaddam

Affiliation: K .N. Toosi University of Technology, Iran, Islamic Republic of

Keyword(s): Adaptive learning algorithms, Feature extraction, Covariance matrix, Gaussian data.

Abstract: In this paper, we present new adaptive learning algorithms to extract optimal features from multidimensional Gaussian data while preserving class separability. For this purpose, we introduce new adaptive algorithms for the computation of the square root of the inverse covariance matrix S - 1 2 . We prove the convergence of the adaptive algorithms by introducing the related cost function and discussing about its properties and initial conditions. Adaptive nature of the new feature extraction method makes it appropriate for on-line signal processing and pattern recognition applications. Experimental results using two-class multidimensional Gaussian data demonstrated the effectiveness of the new adaptive feature extraction method.

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Paper citation in several formats:
Aliyari Ghassabeh, Y. and Abrishami Moghaddam, H. (2007). NEW ADAPTIVE ALGORITHMS FOR OPTIMAL FEATURE EXTRACTION FROM GAUSSIAN DATA. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP 2007) - Mathematical and Linguistic Techniques for Image Mining; ISBN 978-972-8865-75-7; ISSN 2184-4321, SciTePress, pages 182-187. DOI: 10.5220/0002067501820187

@conference{mathematical and linguistic techniques for image mining07,
author={Youness {Aliyari Ghassabeh}. and Hamid {Abrishami Moghaddam}.},
title={NEW ADAPTIVE ALGORITHMS FOR OPTIMAL FEATURE EXTRACTION FROM GAUSSIAN DATA},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP 2007) - Mathematical and Linguistic Techniques for Image Mining},
year={2007},
pages={182-187},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002067501820187},
isbn={978-972-8865-75-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP 2007) - Mathematical and Linguistic Techniques for Image Mining
TI - NEW ADAPTIVE ALGORITHMS FOR OPTIMAL FEATURE EXTRACTION FROM GAUSSIAN DATA
SN - 978-972-8865-75-7
IS - 2184-4321
AU - Aliyari Ghassabeh, Y.
AU - Abrishami Moghaddam, H.
PY - 2007
SP - 182
EP - 187
DO - 10.5220/0002067501820187
PB - SciTePress

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