<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Overview of data store management for sliding-window learning using MLP networks"^^ . "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 employed for modeling and tracking purposes. Sliding-window framework is implemented to combine the robustness of offline learning algorithms with the ability to track recursively the underlying process of a system. This paper view the performance of sliding window backpropagation (SWBP) with application of data store management e.g. simple distance measure, angle evaluation, weighted distance measure, weighted angle evaluation and the novel prediction error displacement. The simulation results show that the best convergence performance is gained using store management techniques. © 2012 IEEE."^^ . "2012" . . "1" . . "ICIAS 2012 - 2012 4th International Conference on Intelligent and Advanced Systems: A Conference of World Engineering, Science and Technology Congress (ESTCON) - Conference Proceedings"^^ . . . . . . . . . . . . . . "N."^^ . "Saad"^^ . "N. Saad"^^ . . "H."^^ . "Izzeldin"^^ . "H. Izzeldin"^^ . . "V.S."^^ . "Asirvadam"^^ . "V.S. Asirvadam"^^ . . . . . "HTML Summary of #2741 \n\nOverview of data store management for sliding-window learning using MLP networks\n\n" . "text/html" . .