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Log-Domain Binary SVM Image Classifier

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5179))

Abstract

We propose in this paper a binary log-domain Support Vector Machine classifier based on a polynomial decision function. To implement such a classifier log-domain multipliers proposed by the authors are used. For the parallel-serial implementation a log-domain summing amplifier and a current mode comparator are also needed. Current mode log-domain design is used for its low voltage, low power and high frequency characteristics. The resulted classifier is simulated taking into account real parameters of transistors in BiCMOS technology.

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Ignac Lovrek Robert J. Howlett Lakhmi C. Jain

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© 2008 Springer-Verlag Berlin Heidelberg

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Groza, R., Festila, L., Hintea, S., Cirlugea, M. (2008). Log-Domain Binary SVM Image Classifier. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85567-5_46

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  • DOI: https://doi.org/10.1007/978-3-540-85567-5_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85566-8

  • Online ISBN: 978-3-540-85567-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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