The data compression course examines the theoretical foundation of compression techniques and algorithms for lossy and lossless data compression as well as signal modeling and its extensions to data compression and applications to multimedia data compression. Topics include basics of signal encoding and decoding for compression, lossy and lossless compression, communication building blocks, and fixed and variable rates, quantization theory including uniform quantization, distortion and bit rate, high rate quantization theory and elementary distortion rate theory, architecture for data compression including signal models and spectral analysis, coding forms, entropy and variable quantization, lossless coding algorithms such as Huffman, arithmetic, universal lossless, adaptive and predictive coding algorithms, distortion and similarity measures, lossy coding algorithms such as scalar quantization algorithm, and vector quantization coding algorithm, speech and audio compression techniques, image and video compression techniques, compression standards and formats.