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Denoising Control Method of Abnormal Signals in Communication Networks Based on Big Data Analysis

In order to improve the denoising control effect of abnormal signals in communication network, a new denoising control method of abnormal signals in communication network based on big data analysis is designed in this paper. The linear prediction model and big data analysis method are used to sample and process the communication network signals, and the abnormal signals in the signal acquisition results are identified. The abnormal signals in communication network are decomposed into multiple IMF components of different time scales by using the empirical mode decomposition method. The IMF dominant component is used to reconstruct the signals, and the reconstructed signals are SWT transformed and median filtered. In this way, the SWT inverse transformation is used to obtain the denoising signals, and the denoising control of abnormal signals in communication network is realized. The simulation results show that the method has high accuracy of abnormal signal identification and denoising control, and the control time is short, and the control effect is better.