A two stage algorithm for the parameters learning of the mixtures of factor analyzers is presented, which first approximates the probability distribution of the data by the Gaussian mixture models, and then performs factor analysis for each Gaussians.
给出了一种用于混合因子分析模型参数学习的两阶段学习算法,即首先使用混合高斯模型学习数据的概率分布,然后对每一个高斯混合项进行因子分析。
参考来源 - Bayes网络模型及其学习算法研究Dynamic fuzzy neural network (D-FNN), through its own parameters learning, changeable topological structure and etc, is able to guarantee the demands for performances under the severe situations arising from the uncertainties inside linear motor and outside disturbances.
动态模糊神经网络控制通过自身所具有的参数学习以及拓扑结构可变等功能,保证在直线电机内部不确定性和外部扰动对系统严重影响的情况下,也能满足性能要求。
参考来源 - 永磁直线同步电机动态模糊神经网络速度控制器设计·2,447,543篇论文数据,部分数据来源于NoteExpress
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