General Motors Advanced Technical Center – Israel
Generalized Gaussian Distributions in Information Theory
This talk will focus on the family of distributions termed Generalized Gaussian (GG). The family of GG distributions has received considerable attention from the engineering community, due to the flexible parametric form of its probability density function, and is used for modeling many physical phenomena. Roughly the talk will consist of three parts. The GG data sources are ubiquitous, thus it is important to understand the fundamental limits of lossy compression of GG sources. In the first part of the talk, we will discuss the lossy compression of GG sources. Closed-form expressions for the rate-distortion curves will be given. The second part of the talk will focus on communication over channels with additive GG noise. The GG distributions can model impulsive noise environments such as acoustic under-water noise and interference in ultrawideband systems with time-hopping. Along the way, we will examine important properties of the GG distribution. The final part is an outlook focusing on open problems and future directions.
The work has been done in collaboration with Alex Dytso, H. Vincent Poor and Shlomo Shamai.