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In a typical adaptive update law, the rate of adaptation is generally a function of the state feedback error.
The desire to include some measurable form of the parameter estimation error in the adaptation law resulted in the development of composite adaptive update laws that are functions of a prediction error and the state feedback.
Parametric uncertainties, unknown coupled dynamics, and bounded external disturbances are compensated online by adaptive update laws.
Moreover, the adaptive update law can be obtained by using the Lyapunov stability theory.
where normalized adaptive update term is μ1e(n)x t)/x T (t)x t) which replaces the adaptive update μe(n)x t) in Equation 4.
Based on this consideration, Piella and Heijmans [17] proposed an adaptive update lifting wavelet (AULW).
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Additionally, the corresponding adaptive updating method can adapt to changes of communication topology, including both exchanging coefficients and updating the identity of participating agents. .
Additionally, the corresponding adaptive updating method can adapt to changes of communication topology, including both exchanging coefficients and updating the identity of participating agents.
The adaptive update-value for RPROP algorithm was introduced as the only factor that determines the size of the weight update.
By this, a decision-directed adaptive updating step should be reasonably forecast.
These conditions are represented in terms of linear matrix inequalities and adaptive updating laws.
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