ADPCM Encoding and Decoding Implementation

This project implements ADPCM (Adaptive Differential Pulse Code Modulation) encoding and decoding using MATLAB. The implementation includes separate m-files for both encoding and decoding operations, following the IMA ADPCM standard algorithm widely used in audio compression applications. The algorithm employs predictive coding and differential encoding techniques for efficient data compression. During the encoding process, the system calculates prediction errors by comparing actual signal sample values with predicted values, then encodes these differences using an adaptive quantizer. The quantization step size dynamically adjusts based on previous samples to optimize compression efficiency. In the decoding phase, the implementation reconstructs original signal samples by processing the encoded differential information alongside prediction values, achieving lossless compression and decompression. The code includes key functions for: - Adaptive step size adjustment based on signal characteristics - Prediction error calculation and quantization - Inverse quantization and signal reconstruction This complete ADPCM implementation provides a practical tool for audio compression research and applications, featuring proper handling of prediction filters and quantization tables as specified in the IMA ADPCM standard. The modular structure allows easy integration with audio processing workflows and supports both educational and practical compression scenarios.