实例研究表明，基于参数优化的自记忆模型提高了自记忆模型的适应性，具有更好的拟合、预测效果。
The example showed that self-memory model, based on parameter optimization, advanced the adaptability and had a better fitting effect and prediction effect.
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。
On the basis of aforesaid work, the author further proposes robust face recognition algorithms based on sparse kernel auto - associative memory models.
对全互连的核自联想记忆模型框架进行了稀疏化改造。
Secondly, the complexity of fully-connected kernel auto-associative memory models is reduced.
设计了一种可控容错域的自联想记忆模型。
A kind of self associative memory model about controllable tolerant fault field is designed.
本文运用反演建模和自记忆性方程相结合的方法，建立了地下水位动态预测模型。
The prediction model of groundwater level dynamics was established using the combinative method of retrieved model and self-memorization equation in this paper.
多值指数关联联想记忆模型（MMECAM）是一种高存储容量的自联想记忆神经网络。
Modified Multi-valued Exponential Correlation Associative Memory Model (MMECAM) is a neural network with higher storage capacity.
多值指数关联联想记忆模型（MMECAM）是一种高存储容量的自联想记忆神经网络。
Modified Multi-valued Exponential Correlation Associative Memory Model (MMECAM) is a neural network with higher storage capacity.
应用推荐