Computer Science – Information Theory
Scientific paper
2011-04-30
Computer Science
Information Theory
Scientific paper
For a long time, detection and parameter estimation methods for signal processing have relied on asymptotic statistics as the number $n$ of observations of a population grows large comparatively to the population size $N$, i.e. $n/N\to \infty$. Modern technological and societal advances now demand the study of sometimes extremely large populations and simultaneously require fast signal processing due to accelerated system dynamics. This results in not-so-large practical ratios $n/N$, sometimes even smaller than one. A disruptive change in classical signal processing methods has therefore been initiated in the past ten years, mostly spurred by the field of large dimensional random matrix theory. The early works in random matrix theory for signal processing applications are however scarce and highly technical. This tutorial provides an accessible methodological introduction to the modern tools of random matrix theory and to the signal processing methods derived from them, with an emphasis on simple illustrative examples.
Couillet Romain
Debbah Merouane
No associations
LandOfFree
Signal Processing in Large Systems: a New Paradigm does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Signal Processing in Large Systems: a New Paradigm, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Signal Processing in Large Systems: a New Paradigm will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-65847