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The most important fact for differential neural networks dynamics is related to its weights time evolution. This is a consequence for the higher nonlinear structure describing the matrix differential equations, which are associated with the adaptive capability for this kind of neural networks. However, as we know, there is no any analytical demonstration of the weights stability. In fact, this is...
In this study the adaptive observing problem for nonlinear uncertain systems is analyzed. The considered nonlinear systems verify the so-called regular form. A new high-order sliding mode neural-observer is suggested to solve the afore-mentioned problem by means of the super-twisting algorithm. This observer is supplied with a new learning procedure which adaptive structure ensuring the practical...
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