Coursera Plus Annual is 40% Off — Ends July 6.

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Positive Semi-Definite Matrices and the Eigenvalues of Their Partitioned Form

NPTEL-NOC IITM via YouTube

Start learning Write review
OpenLearning Ad

Master AI and Machine Learning: From Neural Networks to Applications

Learn More → Scrimba Ad

Free courses from frontend to fullstack and AI

Learn More →

Overview

AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore the fundamental properties of positive semi-definite matrices in this 24-minute lecture that examines how eigenvalues behave when these matrices are partitioned into blocks. Learn why eigenvalues of positive semi-definite matrices are always non-negative and discover the mathematical relationship between the largest eigenvalue of a PSD matrix and the eigenvalues of its constituent blocks. Gain insights into matrix theory concepts that are essential for understanding optimization, numerical analysis, and various applications in engineering and mathematics.

Syllabus

Positive semi-definite matrices and the eigenvalues of their partitioned form

Taught by

NPTEL-NOC IITM

Reviews

Start your review of Positive Semi-Definite Matrices and the Eigenvalues of Their Partitioned Form

Start learning

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.