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The classical Kuhfittig iteration converges strongly under the compactness condition of K, whereas the weak convergence is established through Opial's condition.
Moreover a constructive algorithm for approximations is designed and its convergence is established.
Observer exponential convergence is established under an ad-hoc persistent excitation condition involving the regressor.
Stability is discussed, convergence is established and numerical examples are presented.
Convergence is established using a detailed analysis of the linear-time varying dynamics appearing in the estimation error equation.
The fixed-time convergence is established and the uniform upper bound of the settling time is computed.
Similar(40)
Stability of the predictive iterative learning control system is analyzed and conditions on error convergence are established.
The global convergence and superlinear convergence are established in Section 3 and Section 4, respectively.
With the help of the generalized projections, theorems of strong convergence are established.
Under some assumptions, the global convergence was established for nonconvex optimization problems.
In this section, the error bound and convergence are established by the following lemma.
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CEO of Professional Science Editing for Scientists @ prosciediting.com