Improved Detecting Schemes for Micro-Electronic Devices Based on Adaptive Hybrid Classification Algorithms 


Vol. 38,  No. 6, pp. 504-511, Jun.  2013


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  Abstract

This paper proposes improved detection schemes for concealed micro-electronic devices using clustering and classification of radio frequency harmonics in order to protect intellectual property rights. In general, if a radio wave with a specific fundamental frequency is propagated from the transmitter of a classifier to a concealed object, the second and the third harmonics will be returned as the radio wave is reflected. Using this principle, we exploit the fuzzy c-means clustering and the k-nearest neighbor classification for detecting diverse concealed objects. Simulation results indicate that the proposed scheme can detect electronic devices and metal devices in various learning environments by efficient classification. Thus, the proposed schemes can be utilized as an effective detection method for concealed micro-electronic device to protect intellectual property rights.

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  Cite this article

[IEEE Style]

K. Kim, J. Lim, S. Kim, J. Cho, Y. Shin, "Improved Detecting Schemes for Micro-Electronic Devices Based on Adaptive Hybrid Classification Algorithms," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 6, pp. 504-511, 2013. DOI: .

[ACM Style]

Kwangyul Kim, Jeonghwan Lim, Songkang Kim, Junkyung Cho, and Yoan Shin. 2013. Improved Detecting Schemes for Micro-Electronic Devices Based on Adaptive Hybrid Classification Algorithms. The Journal of Korean Institute of Communications and Information Sciences, 38, 6, (2013), 504-511. DOI: .

[KICS Style]

Kwangyul Kim, Jeonghwan Lim, Songkang Kim, Junkyung Cho, Yoan Shin, "Improved Detecting Schemes for Micro-Electronic Devices Based on Adaptive Hybrid Classification Algorithms," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 6, pp. 504-511, 6. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880