Abstract: Most of existing semi-supervised learning methods heavily depend on labeled samples and always indistinguishably regard all unlabeled instances. However, unreliable samples lying around the ...

Abstract: This work is devoted to the nonasymptotic and robust fractional derivative estimation of the pseudo-state for a class of fractional-order nonlinear systems with partial unknown terms in ...