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Output: Convergence of the RPCD algorithm is given by the following theorem.
Since reliability is a key aspect in this methodology, the paper also focuses on output convergence and method reliability.
This paper considers the global output convergence of Cohen Grossberg neural networks with both time-varying and distributed delays.
This paper discusses the global output convergence of a class of recurrent neural networks with distributed delays.
As in numerous applications of adaptive control, while output convergence is usually guaranteed under feasibility assumptions, little is known about the asymptotic behavior of the parameter estimates themselves.
Based on M-matrix theory, several sufficient conditions are established to guarantee the global output convergence of this class of neural networks.
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An adaptive controller can thus be designed using the Lyapunov approach to achieve output error convergence and boundedness of all signals.
Then, three discriminators including coherent real part method, non-coherent amplitude method and non-coherent power method, are theoretically discussed, and further compared in terms of the output curve, convergence range, gain, mean square error (MSE).
However, as the majority of domesticated plants are selected for increased reproductive output, the convergence between natural r-strategists and domestication in K-strategists seems plausible.
The optimized parameters of f, d, h, and H are output until the convergence conditions are satisfied.
Presumably, countries with strong IOS characteristics will be associated with lower TFP, lower steady-state output, and slower convergence.25.25
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