Number of associative memory networks applied for gray-scale images with random noise is few. Based on MBAM, morphological associative memories of dynamic kernel is presented in this paper.
本文是在MBAM的基础上，提出了一种利用动态核的形态联想记忆网络，其目的是解决含有任意随机噪声图像的联想记忆问题。
Secondly, the complexity of fully-connected kernel auto-associative memory models is reduced.
对全互连的核自联想记忆模型框架进行了稀疏化改造。
On the basis of aforesaid work, the author further proposes robust face recognition algorithms based on sparse kernel auto - associative memory models.
在上述工作的基础上，本文主要研究了基于小世界体系的指数核自联想记忆模型在人脸识别中的应用。
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