Description
Additional focus is placed on concepts like determinants, orthogonality, and least squares solutions. The course often integrates computational aspects, emphasizing tools like MATLAB or Python for practical problem-solving. Advanced topics, including singular value decomposition and applications in signal processing or image analysis, may be covered to enhance the engineering relevance of linear algebra concepts. The goal is to equip graduate engineering students with a solid understanding of linear algebra principles that are crucial for their advanced coursework and professional applications.
Reviews
There are no reviews yet.