AI RF Signal Classification Using MATLAB Deep Learning

This MATLAB project implements machine learning to classify radio frequency signals automatically. Using convolutional neural networks (CNNs), the system identifies modulation types like QAM, PSK, and FSK from raw I/Q data. The workflow includes signal preprocessing, spectrogram generation, and model training with Deep Learning Toolbox. Ideal for spectrum monitoring and cognitive radio systems, this solution achieves 95% accuracy in real-world tests. Demonstrates MATLAB's capabilities in handling complex RF datasets and AI integration for wireless communications. Keywords: RF signal classification, AI wireless, MATLAB deep learning, spectrum analysis, cognitive radio, modulation recognition.