Plots upgedatet, hybirder Ansatz raus

chapter_04.tex

@@ -263,6 +263,7 @@ C_{write\_output} = 5 \\
 \end{equation}
 Equation \ref{equation_computing_final} now provides an estimation of the necessary computing effort for one output sample in relation to the filter length $N$ and the update rate of the filter coefficients $1/U$. This formula can now be used to estimate the needed computing power (and therefore the power consumption) of the \ac{DSP} core for different parameter settings, alowing to find an optimal parameter configuration in regard of the quality of the noise reduction and the power consumption of the system.
 \subsubsection{Performance evaluation of different implementation variants}
+To verify the general performance of the \ac{DSP} implemented \ac{ANR} algorithm, the complex usecase of the high-level implemenation is used, which includes a 16-tap \ac{FIR} filter and an update of the filter coefficients every cycle. In contary to the high-level implementation, the coeffcient convergence is now not included in the evaluation anymore, but the metric for the \ac{ANR} performance stays the same as the \ac{SNR} improvement