The standard derivation error is also calculated.
The problems with them are illustrated and a modification, arising from an earlier trigonometrical derivation error, is also presented and directly paralleled with the original versions.
However, the derivation contains errors which could severely bias the estimation of some components.
But this kind of manual test case derivation is error-prone and knowing these errors makes it possible to provide guidelines to reduce them.
Based on the SNDR derivation, theoretical error performance and statistical channel capacity are provided for this class of methods.
The analytical derivations of error rate, sensitivity and specificity complement the computational formula of Rm2 [25].
This result again validates the assumption that, in the proposed method, the converter time constant can be ignored during the analytic formula derivation with small errors introduced.
For a derivation of discretization errors for such parabolic type problems for a convex combination of the implicit Euler method and the midpoint method, referred to as the θ-method, the following holds (see [14]).
Next to the independence assumption, an asymptotic equivalence is required for this derivation, producing minor errors only for large step-size (short filters) and pdfs that are far from Gaussian.
However their switching curve derivation has an error in the derivatives (Eqs. 7a and 7b of [ 40]) and thus their results are unclear.
