关键词: Kohonen, SOFM, 神经网络, 矢量量化, 图像压缩

Abstract:

The image impression method of vector quantization based on the improved selforganizing feature mapping neural networks is a very efficient way. However, code word cannot be uniformly used. Some neurons never win and the problem of "dead neurons" is still very evident. Kohonen SOFMC is a conscientious competitive learning method. It can maintain the topological invariant map and avoid "dead neurons" most effectively. In this paper, based on the auxiliary SOFMC neurons,a  selforganizing mapping algorithm is proposed. The method is open and you can always add modules into the new effective method to achieve better results. The vector quantization algorithm has been applied to the wavelet transform domain to obtain a better codebook. The simulation results show that the method is better than the existing SOFM method.

Key words: Kohonen;SOFM;neural network;vector quantization;image impression