In the fifth chapter, at first the Wavelet Transformation theory is introduced and used in fusion multi band satellite data. And then combined with the Self-organizing Feature Map Neural Network, in the procedure the vector quantification learning algorithms are presented.
第五章介绍了自组织特征映射神经网络(SOFM)算法与矢量量化学习算法;同时考虑到现在资源卫星采用的高分辨率的全色波段和较低分辨率的多光谱波段结合的发展趋势,研发了小波融合与SOFM分类的组合方法,取得了比较好的效果。
参考来源 - 神经网络及其组合算法的遥感数据分类研究A high robust improved harmonic vector excitation LPC speech coder is proposed by using the improved key algorithm and multi-frame joint vector quantification principle.
利用改进的关键算法和多帧参数联合矢量量化原理设计了一种高鲁棒性的改进型的谐波矢量激励线性预测声码器。
参考来源 - 自适应低速率语音编码关键技术研究·2,447,543篇论文数据,部分数据来源于NoteExpress
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