User-Friendly Tools for Random Matrices: An Introduction

Abstract

Random matrix theory has become a large and vital field of probability, and it has found applications in a wide variety of other areas. To motivate the results in these notes, we begin with an overview of the connections between random matrix theory and computational mathematics. We introduce the basic ideas underlying our approach, and we state one of our main results on the behavior of random matrices. As an application, we examine the properties of the sample covariance estimator, a random matrix that arises in classical statistics. Afterward, we summarize the other types of results that appear in these notes, and we assess the novelties in this presentation.

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Document Details

Document Type
Technical Report
Publication Date
Dec 03, 2012
Accession Number
ADA576100

Entities

People

  • Joel A. Tropp

Organizations

  • California Institute of Technology

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Applied Mathematics
  • Compressed Sensing
  • Data Analysis
  • Data Science
  • Estimators
  • Functional Analysis
  • Graph Theory
  • Information Science
  • Information Theory
  • Linear Algebra
  • Network Science
  • Quantum Information Science
  • Random Variables
  • Signal Processing
  • Theorems
  • Two Dimensional
  • User Friendly

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Statistical inference.
  • Systems Analysis and Design