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Whereas in memristor-based neural networks, to study the dynamic flows of these systems, the classical approach on nonlinear systemic theory is invalid; since it consists of too many subsystems, it is too difficult to do so.
For systems that have no unique linearization equilibria, for example multi-link robot systems, the classical "direct" methods of Fault Tolerant Control (FTC) via fault estimation/compensation cannot easily be achieved via a linear time-invariant systems approach.
For these systems, the classical normalized least-mean-square (NLMS) algorithm which assigns the same step-size to all filter coefficients converges slowly.
Although they can give good predictions for micrometer or larger-size multiphase systems, the classical models usually underestimate the enhancement of thermal conductivity increase of nanofluids as a function of volume fraction.
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Narrow band constraining of the transmission affects the BER of the system (the classical feature of a phase-modulated signal).
Since the viscoelastic terms, nonlinear damping and source terms are included in the system, the classical method employed in single equation cannot be directly used to prove the blow-up result.
We know that, in MIMO system, the classical combining technique is maximum ratio combining (MRC) [19], where the signals from the received antenna elements are weighted such that the output SNR is maximized.
Three distinct pathways constitute the complement system; the classical pathway, the alternative pathway and the lectin pathway [1].
Three biochemical pathways activate the complement system: the classical complement pathway, the alternative complement pathway, and the mannose-binding lectin pathway [14].
There are three pathways to activate the complement system: the classical, alternative, and lectin pathways.
There are three pathways in the Complement system: the classical pathway, the lectin pathway, and the alternative pathway.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com