矢量量化是圖像壓縮的重要方法。論文提出了基于Hopfield 神經網絡的圖像矢量量化方法，該方法首先構造聚類表格；然后聚類表格按離散Hopfield 神經網絡串行方式運行；
最后根據得到的最終碼字集，對圖像進行矢量量化。論文最后給出模擬實驗和結果比較，結果表明該方法是有效的，生成的碼本質量優于傳統的LBG 算法。
關鍵詞：矢量量化；碼本；LBG 算法；Hopfield 神經網絡
Abstract：Image vector quantization is an important method in the image compression field. This paper proposed a method of image vector quantization based on hopfield Neural Network.This method first built a clustering form; then the clustering form worked according to the asynchronous mode of discrete hopfield neural network; Finally carried on the image vector quantization according to the final codebook set. The paper finally produced the
experiments and the result comparison, the result indicated this method is effective and the codebook quality surpassed traditional the LBG algorithm.
Key Words：Vector Quantization; Codebook ;LBG Algorithm; Hopfield Neural Nework1