# Noise Reduction Method of Nanopore Based on Wavelet and Kalman Filter
## 4 Results and Discussion  
Through the above analysis of the Kalman filter algorithm, wavelet mode maxima method effectively improves the estimation accuracy of Kalman filter, so this paper combines both wavelet mode maximization method and Kalman filter algorithm to apply in the noise reduction processing of nanopore current signal, and the comparison of processing effect with traditional Kalman filter algorithm is shown in Figure 7a,b, and it is found that the combined algorithm not only improves the accuracy of [PERSON] filter algorithm, but also improves the noise reduction effect significantly. The red area is the processing result of the current signal after the noise reduction processing (c). Applying the above two methods to the whole segment of IgG current signal, it is found that the traditional Kalman filter process brings a false peak of noise P0, and the Kalman filter process based on the wavelet mode maxima method proposed in this paper eliminates this peak better, which makes the characteristic peak PI of IgG antibody current signal stand out, which is significant for analyzing the characteristics of IgG antibody. Additionally, by comparing the standard deviation (RMS) of this method with the traditional Kalman filter processing method, as shown in Table 2, the measured data shows that the method proposed in this paper reduces the standard deviation of the background noise by 17.8%, which is better than the traditional Kalman filter.  
Figure 6: After wavelet processing, then the signal is processed by Kalman filter: (**a**) part of the current signal; (**b**) the wavelet transform improves the accuracy of Kalman filtering, makes the estimated value of Kalman filtering tend to the real value, and ensures the accuracy of data estimation; (**c**) in the long-term estimation, the Kalman filter maintains a stable and small error, and has a great effect on the noise reduction of the nanopore signal.  
The experimental results show that the noise reduction treatment of the nanopore current signal is completed by using the method based on wavelet transform and Kalman filter, which is better than traditional Kalman filter in terms of estimation accuracy and noise reduction, and the traditional Kalman filter algorithm may misclassify the noise signal as valid signal, which has a great impact on the analysis of biomolecular properties. which is based on the traditional Kalman filter, combined with the characteristics of multi-scale analysis of wavelet transform, and the noise reduction effect is better in the low and high frequencies are estimated separately. The noise reduction effect is good and has high reference significance for the noise reduction of molecular perforation signal of nanopore detection system.  
Conceptualization, Z.H.; Data curation, X.Z.; Methodology, Z.H.; Software, Z.H.; Writing--original draft, D.W. and S.F.; Writing--review & editing, D.W. and S.F. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Outstanding Youth Fund of Chongqing Municipal Science Committee: cstc2021 jcyjqX0030; Natural Science Foundation of Beibei District, Chongqing: E1316101.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Traditional Kalman Filter** & **Kalman Filter Based on Wavelet Mode Maxima** \\ \hline RMS & 186.2378 & 152.9993 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of RMS.  
Figure 7: (**a**) Traditional Kalman filter fragment processing results; (**b**) Kalman filter fragment processing results based on wavelet mode maxima; (**c**) traditional Kalman filter processing distribution of experimental signal; (**d**) Kalman filter processing distribution based on wavelet mode maxima of experimental signal.