Information Theory and Coding cam
This is a PDF document written by
J.G. Daugman on the fundamentals of the theory of information and coding.
Beginning with the very basic concept of probability and uncertainty, and the
concept of information, it arrives at entropies and their meaning. It deals with
the source coding theorems: prefix, variable-length, and fixed-length codes. It
looks into several kinds of channels, their properties, noise, and channel
capacity. The further topics delve into detail with continuous information,
noisy channel coding theorems, Fourier series elaborated on in making matters of
convergence, orthogonal representation, and useful Fourier theorems. The text
also expands into aspects such as sampling and aliasing, DFT, FFT algorithms,
and the quantized degrees-of-freedom in continuous signals and concludes with
discussions on the Gabor-Heisenberg-Weyl uncertainty relation and Kolmogorov
complexity for a general overview of some of the key principles of information
theory and coding.
Author(s): J G Daugman
75 Pages