EECS 651
Source Coding Theory
Winter, 2001


Source coding (i.e. data compression) is the process of creating binary rep- resentations of the data from sources such as speech, images, audio, video or English text. This course gives a broad introduction to the theory and practice of lossy coding (i.e. quantization), where perfect reproductions are not possible or require too many bits (e.g. speech, images, audio, video) and also of lossless coding, where perfect reproductions are required (e. g. text). The lossy codes include scalar, vector, transform (e.g. JPEG, MPEG), subband (e.g. wavelet), predictive and adaptive quantizers (e.g. CELP); and the theory is mainly high resolution quantization theory. The lossless techniques include Huffman, run-length, Lempel-Ziv, and arithme- tic codes; and the theory is entropy theory. Particular attention is paid to coding speech and images. Students will gain experience in source coding through a term project. The course is oriented toward first and second year graduate students. It is a kernel course for both communications and signal processing. No previous introduction to source coding is presumed. Detailed Syllabus (attached)

Time and Place

MWF 1:30-2:30, 3150 Dow (but it may change)


Prof. David L. Neuhoff
4215 EECS Building

Office hours

Course Syllabus

Course Details


There is no required course textbook. You should, however, obtain a copy of the following paper: R.M. Gray and D.L. Neuhoff, "Quantization," IEEE Trans. Inform. Theory, pp. 2325-2383, Oct. 1998. You may download it from IEEE through the library web page:, or directly by clicking here. See also the list of books on reserve for the class in the Media Union. Those in bold are likely to be the most useful references.

Reference List

Books on reserve in the Media Union

Lectures, Notes and Handouts

Winter 1999 Lectures, Notes and Handouts


Term Projects