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This paper presents an overview of sliding-window based learning with data store management (DSM) techniques using multilayer perceptron (MLP) neural network. The paper views several DSM techniques used to reduce the correlation of data inside the window store. The sliding window (SW) training is a form of higher order instantaneous learning strategy without the need of covariance matrix, usually...
This paper presents real time nonlinear system identification with irregular sampling time or lost packets. This work views the performance of predictive MLP neural network using sliding window learning approach. By adopting nonlinear autoregressive with external input (NARX) model order, this paper investigate the response of sliding window leaning when the measurement received by the MLP network...
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