ENGG 5781 Matrix Analysis and Computations
Term
1, 2018-19


Announcement

 


 

General Information

Instructor

Prof. Wing-Kin (Ken) Ma  

 

Time and Venue

Lecture: Monday 11:30am--12:15pm, Yasumoto International Academic Park LT7
                Tuesday 4:30pm--6:15pm, Mong Man Wai Building Room 710  

 

Course Description

Matrix analysis and computations are widely used in engineering fields --- such as machine learning, computer vision, systems and control, signal and image processing, optimization, communications and networks, and many more --- and are considered key fundamental tools. This course covers matrix analysis and computations at an advanced or research level. It consists of several parts. The first part focuses on various matrix factorizations, such as eigendecomposition, singular value decomposition, Schur decomposition, QZ decomposition and nonnegative factorization. The second part considers important matrix operations and solutions such as matrix inversion lemmas, linear system of equations, least squares, subspace projections, Kronecker product, Hadamard product and the vectorization operator. Sensitivity and computational aspects are also studied. The third part explores presently frontier or further advanced topics, such as matrix calculus and its various applications, tensor decomposition, and compressive sensing (or managing undetermined systems of equations via sparsity). In every part, relevance to engineering is emphasized and applications are showcased.

Assessment

 

Learning Resources

Lecture notes in slide form, as well as supplementary materials, are provided; please check this course website regularly.

Recommended readings:

 


Lecture Notes

 

Assignments

 

Assignment Solution