Assymetric Lossless Compression via Algorithmic Self-organizing Structures

This internship project with Deep Compression Inc. aims to produce a prototype demonstrating a new technique for asymmetric lossless data compression. Unlike conventional compression techniques, this prototype will allow representational information to be recovered using an algorithmic recovery procedure, algorithmic self-organizing structure (ASOS). This new approach could pave the way for previously unprecedented levels of data compression – a potentially revolutionary technology with the likelihood of affecting such diverse sectors as mathematics, life sciences, computing science, geoinformatics, the environment and the entertainment industry.

Faculty Supervisor:

Dr. Hugh Williams

Student:

Kjell Wooding

Partner:

Deep Compression Inc.

Discipline:

Engineering

Sector:

Information and communications technologies

University:

University of Calgary