摘要
该文首先分析了五类湖底回波的不同尺度下小波子空间的能量特征和分形维特征;然后将这些特征矢量作为分类的特征,并根据特征本身的离散程度对其进行加权;最后采用最小距离分类器对其进行分类,取得了 96.11％的分类正确率。
Firstly, the energy distribution in different wavelet scale space and the fractal dimension of underwater sonar echoes are discussed. Then, these feature vectors are utilized to classify the real echoes, and weight these features according to their own degree of dispersion. Finally, a minimum distance classifier is used in the classification procedure, and experimental results demonstrate the efficiency of the method.
出处
《电子与信息学报》
EI
CSCD
北大核心
2003年第6期844-846,共3页
Journal of Electronics & Information Technology
