摘要
形态联想记忆网络具有良好的联想记忆功能和较强的抗膨胀或腐蚀噪声能力,但抗混合噪声的能力很弱。而在实际中,随机噪声往往是混合型的,既有膨胀又有腐蚀噪声,将尺度空间和形态联想记忆网络相结合,得到了一种新的联想记忆网络,它提高了形态自联想记忆网络的抗随机噪声能力。通过仿真实验验证了该方法具有良好的性能。
Morphological associative memories （MAM） has strong associative memorizing ability and fairly strong capability against dilative or erosive noise, but its ability against general noise is poor. But in practice, random noise is always composed both of dilative and erosive noise. It is proposed that scale space and MAM is combined to get a new version of MAM with improved noise resisting ability. The results of emulation experiment testify it good performance.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第11期2662-2664,共3页
Computer Engineering and Design
基金
江苏省自然科学基金项目(BK2003017)。
关键词
形态学
尺度空间
自联想记忆
膨胀存储矩阵
腐蚀存储矩阵
morphology
scale space
auto-associative memories
dilative memory matrix
erosive memory matrix
