NDLI: Reduced polynomial classifier using within-class standardizing transform

Content Provider	IEEE Xplore Digital Library
Author	Scarano, G. Forastiere, L. Colonnese, S. Rinauro, S.
Copyright Year	2012
Description	Author affiliation: DIET, Università “La Sapienza” di Roma, via Eudossiana 18 00184 Roma, Italy (Scarano, G.; Forastiere, L.; Colonnese, S.; Rinauro, S.)
Abstract	In this paper we introduce a novel, reduced dimension, Polynomial Regression based Classifier (PRC). The classical PRC expands the observed feature data set by considering higher order data statistics. The herein presented novel PRC preliminary performs projections of the data on suitable subspaces associated with the different classes. The projection operation is followed by discarding the contributions due to the higher order mixed sample moments evaluated on the data. Thereby, the overall polynomial approximation order is maintained while the dimensionality of the expanded feature space exploited by the reduced dimension classifier is drastically reduced. We assess the performance of both the full and the reduced PRC by numerical simulations on different scenarios. The reduced dimension PRC performs at least as well as the classical PRC with a significantly lower number of involved terms. This paves the way for extensively exploiting the PRC flexibility and applicability to complex classification problem although in resource limited system environments, such as, for instance, real-time applications on FPGAs.
Starting Page	1
Ending Page	4
File Size	418446
Page Count	4
File Format	PDF
ISBN	9781467302746
e-ISBN	9781467302760
DOI	10.1109/ISCCSP.2012.6217825
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-02
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Numerical simulation Polynomials Vectors Matrices Approximation methods Computational complexity
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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