Modulation Scheme Recognition Using Decision-Theoretic Methods in MATLAB

This MATLAB implementation utilizes decision-theoretic methods for modulation scheme recognition, supporting identification of multiple modulation types including but not limited to AM (Amplitude Modulation), FM (Frequency Modulation), USB (Upper Sideband), LSB (Lower Sideband), ASK (Amplitude Shift Keying), PSK (Phase Shift Keying), and FSK (Frequency Shift Keying). The approach involves extracting statistical features from signal waveforms (such as instantaneous amplitude, frequency, and phase characteristics) and applying pattern classification algorithms to accurately determine modulation types. Key MATLAB functions like signal preprocessing, feature calculation using statistical moment analysis, and decision tree or Bayesian classifiers enable precise modulation identification, facilitating better understanding and analysis of signal characteristics and applications. The implementation typically includes signal segmentation, feature vector generation, and classification threshold optimization to handle real-world signal variations.