Quadratic Forms in Gaussian Random Variables: A Survey of Theoretical Results and Applications
Quadratic Forms in Gaussian Random Variables (QFGRV) appear in a wide variety of applications in signal processing, communications, performance and reliability engineering, genetics, etc.
Overview
Abstract
Quadratic Forms in Gaussian Random Variables (QFGRV) appear in a wide variety of applications in signal processing, communications, performance and reliability engineering, genetics ... etc. There is a vast amount of literature related to computing various statistical quantities related to QFGRV. In this talk we present how quadratic forms in gaussian random variables arise in various fields and discuss why they are challenging to compute efficiently. We classify the literature on QFGRV based on the parameters of the QFGRV, computational properties and other aspects of interest. We highlight several open problems related to computational limits and error bounds of QFGRV.
Brief Biography
Mohanad Ahmed is a Research Specialist in the Information Science Lab at King Abdullah University of Science and Technology. His work is in the development of signal processing algorithms and embedded systems for navigation and localization applications. In the area of outdoor navigation, he mostly works on attitude determination of vehicles from Global Navigation Satellite System signals. In the area of indoor navigation, he works mostly on signal processing algorithms for ultrasonic and ultrawideband systems. Mohanad Ahmed received a B.Sc. degree in Electrical and Electronic Engineering from the University of Khartoum, Khartoum, Sudan, in 2011 and an M.Sc. degree in electrical engineering from the King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, in 2015. Between 2016 and 2018, he was a Lecturer at the University of Khartoum.