Constructing Neural Networks Using Wavelet Functions

This program implements source code for constructing neural networks using wavelet functions. The source code finds broad applications in signal processing domains, particularly for analyzing electrocardiogram (ECG) signals, electroencephalogram (EEG) signals, and other types of biological signals. By leveraging wavelet transforms within the neural network architecture, the system effectively extracts crucial signal features through multi-resolution analysis and implements classification algorithms for accurate pattern recognition. This makes the program a powerful tool for researchers and medical professionals, enabling deeper insights into physiological conditions and supporting disease diagnosis and treatment planning. The implementation includes customizable parameters for wavelet decomposition levels and neural network configurations, allowing users to tailor analyses to specific requirements. With a user-friendly interface and flexible architecture, this source code serves as a versatile and robust tool that plays significant roles in advanced signal processing applications.