A noise reduction processing method and system suitable for experimental data

Abstract

The invention discloses a noise reduction processing method and system applicable to experimental data. The method comprises the steps of 1, obtaining a data text to be processed; 2, converting data of the data text into a one-dimensional set; 3, after difference absolute values between adjacent elements in the one-dimensional set are obtained through calculation, an average value of all difference absolute values is calculated, and according to the average value, a judging threshold value is calculated according to the average value; 4, after the difference absolute values and the judging threshold values are compared, an initial position and an ending position of each noise point are obtained; 5, halving iteration processing of the difference absolute values is performed on each noise point till each difference absolute value of the noise point is lower than the judging threshold value. The calculated amount is small, the operating rate is high, noise reduction processing can be performed on experimental data automatically, rapidly and efficiently, and the noise reduction processing method and system can be widely applied to the experimental data processing industry.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a noise reduction processing method and system suitable for experimental data. Background technique [0002] At present, during the experimental testing of the molecular interaction of the sample, in order to accurately reflect the changes in the sample during the experimental process, a large amount of experimental video data is usually measured and monitored by experimental instruments (such as PLEXERA’s biomolecular interaction analyzer), and then The video data is processed by the supporting analysis software, and the gray value of multiple selected points in the video is obtained per second. The gray value group of each point reflects the change of the sample during the experiment. These points are depicted as a line graph, through which the entire change process of the experiment can be clearly observed, so that the experimental results can be obtained by comparing the line g...

AI Technical Summary

Problems solved by technology

However, during the experiment, the gray value of the sample detected by the monitor will fluctuate due to accidental light source deviation, which makes some noise points appear in the gray value group, and the noise data here is like a "glitch" on the line graph , these noise points appear randomly due to the deviation of the light source of the monitor. At present, the supporting software of the experimental instrument has no way to deal with these noise points. Although the noise points are only a small part, these noise points will still affect the final fitting result of the experiment.

At present, in order to eliminate these noise points, it is necessary to manually adjust the operation. After many experiments, the purpose of eliminating noise points is achieved. This method takes a long time to operate and the experiment efficiency is low.

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