Research on the Joint Optimization of Traditional Chinese Medicine Pulse Signals Based on BP Neural Networks and Adaptive Filters

TCM (Traditional Chinese Medicine) pulse diagnosis is an important part of traditional Chinese medical diagnosis, carrying rich clinical information. To address the randomness and complex non-stationarity of pulse signal processing, a new technique for the joint optimization of TCM pulse signals based on BP neural networks and adaptive filters (LMS) is proposed. Traditional signal processing methods often fail to effectively denoise and classify signals, limiting the accuracy of pulse analysis. The adaptive filtering algorithm, combined with the advantages of neural networks, can dynamically adjust the filter parameters in real time to adapt to the dynamic changes of pulse signals. This study explores its applications in pulse signal denoising, feature extraction, and classification, thereby improving the accuracy and efficiency of signal processing. It also provides more reliable support for TCM diagnosis, advancing the modernization of TCM.