Recursive Incremental Gaussian Mixture Network For Spatio-Temporal Pattern Processing

ChemBioChem(2016)

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摘要
This work introduces a novel neural network algorithm for online spatio-temporal pattern processing, called Echo State Incremental Gaussian Mixture Network (ESIGMN). The proposed algorithm is a hybrid of two stateof-the-art algorithms: the Echo State Network (ESN), used for spatio-temporal pattern processing, and the Incremental Gaussian Mixture Network (IGMN), applied to aggressive learning in online tasks. The algorithm is compared against the conventional ESN in order to highlight the advantages of the IGMN approach as a supervised output layer. Resumo. Este trabalho introduz um novo algoritmo de redes neurais para processamento online de padroes espaco-temporais, chamado Echo State Incremental Gaussian Mixture Network (ESIGMN). O algoritmo proposto e um hibrido de dois algoritmos estado-da-arte: a Echo State Network (ESN), usada para processamento de padroes espaco-temporais, e a Incremental Gaussian Mixture Network (IGMN), aplicada ao aprendizado agressivo em tarefas online. O algoritmo e comparado com a ESN convencional a fim de destacar as vantagens da abordagem IGMN como camada supervisionada de saida.
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