Algorithms for lossy/lossless compression and error-correcting codes have been at the core of the digital revolution. This project focuses on the particular set of applications in which both lossy compression and noise resilience are required. Examples include storage of high resolution imagery on non-perfect semiconductor (flash) memory and real-time video surveillance over jammed or noisy channels.
The state-of-the art solution is "separation": serial concatenation of an off-the-shelf compression algorithm with an off-the-shelf error-correcting code. However, as shown recently by the investigators, for worst-case guarantees the separated solution is far from being (even asymptotically) optimal. This provides the principal motivation for a multifaceted investigation of the combinatorial, geometric, algebraic and information theoretic aspects of the joint source-channel coding problem.
The breadth of mathematics will be appealing to young researchers with a wide variety of backgrounds, and will help attract new talent to the field. Creation of sophisticated source-channel codes with dependable guarantees is expected to have technological impact in military, space exploration, natural science, and consumer applications.
