Equal-Average Equal-Variance Equal-Norm Nearest Neighbor Search Algorithm for Vector Quantization
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概要
- 論文の詳細を見る
A fast nearest neighbor codeword search algorithm for vector quantization (VQ) is introduced. The algorithm uses three significant features of a vector, that is, the mean, the variance and the norm, to reduce the search space. It saves a great deal of computational time while introducing no more memory units than the equal-average equal-variance codeword search algorithm. With two extra elimination criteria based on the mean and the variance, the proposed algorithm is also more efficient than so-called norm-ordered search algorithm. Experimental results confirm the effectiveness of the proposed algorithm.
- 社団法人電子情報通信学会の論文
- 2003-03-01
著者
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Lu Zhe-ming
Department Of Automatic Test And Control Harbin Institute Of Technology
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SUN Sheng-He
Department of Automatic Test and Control, Harbin Institute of Technology
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Sun Sheng-he
Department Of Automatic Test And Control Harbin Institute Of Technology
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