Observer-Based State Estimation for Recurrent Neural Networks: An Output-Predicting and LPV-Based Approach
Wanlin Wang,
Jinxiong Chen,
Zhenkun Huang
Abstract:An innovative cascade predictor is presented in this study to forecast the state of recurrent neural networks (RNNs) with delayed output. This cascade predictor is a chain-structured observer, as opposed to the conventional single observer, and is made up of several sub-observers that individually estimate the state of the neurons at various periods. This new cascade predictor is more useful than the conventional single observer in predicting neural network states when the output delay is arbitrarily large but… Show more
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