Vector Quantization of Reference Signals for Efficient Frame-Based Classification of Underwater Transient Signals 


Vol. 34,  No. 2, pp. 181-185, Feb.  2009


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  Abstract

When we classify underwater transient signals with frame-by-frame decision, a database design method for reference feature vectors influences on the system performance such as size of database, computational burden and recognition rate. In this paper the LBG vector quantization algorithm is applied to reduction of the number of feature vectors for each reference signal for efficient classification of underwater transient signals. Experimental results have shown that drastic reduction of the database size can be achieved while maintaining the classification performance by using the LBG vector quantization.

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  Cite this article

[IEEE Style]

T. G. Lim, T. H. Kim, K. S. Bae, C. S. Hwang, "Vector Quantization of Reference Signals for Efficient Frame-Based Classification of Underwater Transient Signals," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 2, pp. 181-185, 2009. DOI: .

[ACM Style]

Tae Gyun Lim, Tae Hwan Kim, Keun Sung Bae, and Chan Sik Hwang. 2009. Vector Quantization of Reference Signals for Efficient Frame-Based Classification of Underwater Transient Signals. The Journal of Korean Institute of Communications and Information Sciences, 34, 2, (2009), 181-185. DOI: .

[KICS Style]

Tae Gyun Lim, Tae Hwan Kim, Keun Sung Bae, Chan Sik Hwang, "Vector Quantization of Reference Signals for Efficient Frame-Based Classification of Underwater Transient Signals," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 2, pp. 181-185, 2. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880