Lecture 4 | Introduction to Linear Dynamical Systems

Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on orthonormal sets of vectors and QR factorization for the course, Introduction to Linear Dynamical Systems (EE263).

Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions.

Complete Playlist for the Course:
http://www.youtube.com/view_play_list?p=06960BA52D0DB32B

EE 263 Course Website:
http://www.stanford.edu/class/ee263/

Stanford University:
http://www.stanford.edu/

Stanford University Channel on YouTube:
http://www.youtube.com/stanford/

Category:

Education

Tags:

• science
• electrical
• engineering
• technology
• linear
• dynamical
• system
• orthonormal
• vector
• matrix
• dual
• basis
• Cauchy-Schwartz
• inequality
• research

[darfunkelidas]

Great teacher, any other guy would make u sleep.

[dalahmah]

Anyways, he talked about range of matrices, spans, basis, inner product, norm, orthonormal vectors.

[dalahmah]

did u notice that he skipped the slise of "full rank matrices" around time 48 min

[threelegduck]

this still looks like algebra to me, if i may biject