Music Signal Processing and Optimization Algorithm Based on Wavelet Neural Network Model

In this article, the application of CAD (Computer Aided Design) technology and WNN (Wavelet Neural Network) model in music signal processing is studied, and the principle, method, and optimization ability to improve processing efficiency are explored. A music signal processing and optimization algorithm based on CAD and WNN model is constructed, and simulation experiments verify its effectiveness. Through comprehensive analysis, it is found that this model has good performance in music classification tasks, and its accuracy and processing efficiency are obviously higher than those of SVM (Support Vector Machine) and RNN (Recurrent Neural Network) algorithms. This is mainly due to the powerful feature detection and classification capabilities of CAD and WNN models, which can better capture the complex patterns and features in music signals. In contrast, SVM and RNN algorithms have some limitations when dealing with music classification tasks and can't make full use of the information in audio signals. Through research, this article provides a new idea and method for researchers in the field of music signal processing, which promotes the growth of this field. © 2024 U-turn Press LLC.