EE1030/EE2100 Matrix Theory

Welcome to the official webpage of the course EE1030/EE2100 (Matrix Theory).

This undergraduate course introduces core concepts in linear algebra and explores their applications across various disciplines, primarily Electrical Engineering, with some examples from Machine Learning.

Course Contents : Introduction to vectors, elementary operations on vectors, Dot product, Norm of a vector, Cauchy-Schwarz inequality, Projection, Vector Space, Subspace, Linear Combination, Span, Linear independence, Spanning Set, Basis, Orthogonal basis, representation of a vector in orthogonal basis, Gram-Schmidt Algorithm, projection of a vector onto subspace, K-means Clustering, Introduction to Matrices, Matrix-Vector Product, Linear Transformations, Inverse of a Matrix, Matrix Multiplication, Fundamental Subspaces of Matrix, System of Linear Equations, Rank-Nullity Theorem, Gaussian Elimination, LU decomposition, Overdetermined System of Linear Equations, Linear Regression, Trace of a matrix, Determinant of a matrix, Eigen Values and Eigen Vectors, Spectral Theorem, Rayleigh quotient, Quadratic Forms, Positive Definite matrices, Positive semidefinite matrices, Cholesky decomposition, QR decomposition, Singular value decomposition (SVD), Matrix Norms and Principal component Analysis.

The objective of the course is to explore applications associated with the concepts covered. Some applications are covered in the main lectures, while others are introduced through the practice problem sets.

Instructor

• Name : Seshadri Sravan Kumar V

• Email : seshadri@ee.iith.ac.in

• Office : EE603, Electrical Engineering

Class Timings

• Class timings : Slot D (Monday 12:00 - 12:55, Tuesday 09:00 - 09:55 and Friday 11:00 - 11:55)

• Venue: LHC-03, Lecture Hall Complex

Evaluation Pattern

• Checkpoint Quizzes : 10%

• Quizzes : 30% (Top 3 scores will be considered)

• Exams : 60% (25% for Mid-Term and 35% for Final Exam)

References

• Gilbert Starng, “Linear Algebra and its applications”, Cengage Learning

• S H FriedBerg, A J Insel, L E Spence, “Linear Algebra”, PHI Learning

• S Boyd and L Vandenberghe, “Introduction to Applied Linear Algebra”, Cambridge university press [ebook available on Prof. Boyd’s Webpage]

• E Kreyszig, “Advanced Engineering Mathematics”, Wiley.

• M Greenberg, “Advanced Engineering Mathematics”, Pearson

Teaching Assistants

Credit to the following undergraduate students who have volunteered to serve as Teaching Assistants for the course.