As a derivative method of PLS, multiway partial least square ( MPLS ) method is widely used in batch process modeling. 做为PLS的一种衍生方法,多向偏最小二乘(MPLS)方法在间歇过程建模方面取得了广泛应用。
To reduce the computational complexity of volterra on-line identification that based on the batch least square algorithm and to void the correlation matrix becoming ill-conditioned, a recursive batch least square based Volterra identification method is proposed in this paper. 针对用批量最小二乘方法进行Volterra级数在线辨识计算量大,所需数据存储空间多,以及实际应用时自相关矩阵易出现病态的不足,提出了一种基于递推批量最小二乘的Volterral级数辨识方法。
To reduce the computational complexity of Volterra series on-line identification based on batch least square filter, and to save the data store spaces needed, an identification method based on recursive batch least square filter was proposed and applied to nonlinear fault diagnosis. 针对批量最小二乘在线辨识Volterra级数存在计算量大,数据存储空间占用多的不足,提出了一种基于递推批量最小二乘的辨识方法。