MATLAB-Implemented ADPCM Codec with Algorithmic Enhancements

This ADPCM codec implementation utilizes MATLAB, a high-level programming language extensively employed in engineering computations and signal processing applications. The system employs a sophisticated adaptive algorithm that continuously analyzes audio signal patterns to predict subsequent sample values. Key implementation aspects include: The encoder component processes raw audio signals through difference computation between actual and predicted values, followed by adaptive quantization using a scaling factor that dynamically adjusts based on signal characteristics. The quantization index is then encoded for storage or transmission. The decoder reconstructs the original signal by performing inverse quantization and prediction correction, maintaining synchronization with the encoder's adaptive step-size adjustments. The implementation features: - Adaptive step-size control algorithm using a state machine for efficient bit-rate reduction - Differential coding mechanism that calculates differences between consecutive samples - Quantization tables optimized for voice frequency ranges (300-3400 Hz) - Frame-based processing with configurable buffer sizes for real-time applications This codec architecture demonstrates particular effectiveness in telecommunications systems and digital audio recording applications, where its balance between compression efficiency (typically 4:1 ratio for 16-bit to 4-bit conversion) and reconstructed audio quality makes it valuable for professional audio engineering workflows. The MATLAB implementation includes configurable parameters for sampling rates, quantization levels, and adaptation speed controls.