Many systems of equations are non-linear, and knowing how to solve these non-linear systems is important. In this lesson, learn how to recognize...
The proposed model has been formulated to take into account the material damage evolution at different load levels and it allows the effect of the loading sequence to be included; by means of a recurrence formula derived for multilevel loading, complex load sequences can be considered. The ...
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The integration of Q-learning and the non-linear hunting scheme into GJO provides a multi-faceted enhancement: (i) Q-learning allows the algorithm to adapt based on past experiences, making more informed decisions over time, (ii) The non-linear hunting scheme ensures a diverse population, avoi...
These coefficients were subsequently used to train a cascaded Linear Discriminant Analysis (LDA)-based classifier. The method presented in [18] followed an approach similar to [17] for the detection of humans in image sequences, where NMF was employed to learn a set of pose primitives. In [...
Issue DateSeptember 1969 DOIhttps://doi.org/10.1007/BF02849488 Keywords Asymptotic Expansion Difference Equation Hypergeometric Function Recursion Formula Asymptotic Series Access this article Subscribe and save Springer+ Basic €32.70 /Month Get 10 units per month ...
The selection of relevant coefficients in the formula is very important. The transformer used in this paper is a dry-type transformer with a capacity of 100 kVA. During the experiment, kp and r are taken as 20, 100 respectively, kq and s are taken as 0.15 and 30 respectively. The above...
This has been achieved by approximating the amplitude-to-amplitude (AM/AM) and amplitude-to-phase (AM/PM) curves; unfortunately, the formula utilizes Bessel series expansion and perfect predistortion scenarios. The BER degradation in a solid-state power amplifier using Rapp’s model as a function...
Formula 2: P value calculation for the Functional Impact (FI) module. In a final step, RE and FI P values are combined using the Fisher method (Formula 3). $${{{\rm{T}}}=-2 * \left[{ln}\left({{RE}}_{p-{value}}\right)+{ln}\left({{FI}}_{p-{value}}\right)\right]$...
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