Anomalous signal recognition algorithm for electronic communication equipment based on improved gradient projection method

In the operation process of electronic communication equipment, the transmission of signals is very susceptible to strong interference by external factors, and the conventional signal recognition method has the problem of inaccurate identification of abnormal signals in the application. For this reason, this paper proposes an abnormal signal recognition algorithm for electronic communication equipment based on the improved gradient projection method. First, the electronic equipment signal data is preprocessed, and the deep learning method is used to extract signal features. Then, based on the signal model and the extracted signal features, the improved gradient projection (IGP) method is used to realize the accurate recognition of abnormal signals of electronic communication equipment. For different types of electronic communication equipment signals, the signal anomaly recognition accuracy of this paper’s method is greater than 97%, indicating that the method can effectively recognize multiple types of electronic communication equipment signal anomaly problems. At the same time, the recognition accuracy of this paper’s method for abnormal signals is better than that of traditional recognition methods in different signal partitions and different experimental times, and the average value of the recognition correct rate is 32.24% higher than that of traditional methods, which fully demonstrates that this paper’s method has better recognition performance and higher recognition stability in the recognition of abnormal signals of electronic communication equipment.