A Filtering-Based Stochastic Gradient Estimation Method for Multivariate Pseudo-Linear Systems Using the Partial Coupling Concept

Solutions for enhancing parameter identification effects multivariate equation-error systems in random interference and coupling conditions are considered this paper. For the purpose of avoiding impact colored noises on precision, an appropriate filter is utilized to process autoregressive moving average noise. Then, filtered system transformed into a number sub-identification models based output dimensions. Founded negative gradient search, new filtering algorithm employing partial approach proposed, conventional derived comparison. Parameter has high estimation accuracy efficient calculation speed with application data method. Two simulations performed reveal proposed method’s effectiveness.