Advanced Matrix Theory and Linear Algebra for Engineers

Delve into an extensive course on advanced matrix theory and linear algebra tailored for engineers. Explore key concepts including singular value decomposition, linear systems, Hermitian and symmetric matrices, diagonalization, inner product and orthogonality, linear transformations, basis, linear independence, subspaces, and vector spaces. Progress through multiple parts of each topic, gaining a comprehensive understanding of these advanced mathematical concepts and their applications in engineering. Enhance your problem-solving skills and analytical abilities through this in-depth exploration of matrix theory and linear algebra.

Syllabus

Singular Value Decomposition (SVD) Part 1 (CH_30).
Back To Linear Systems Part 2 (Ch-30).
Back To Linear Systems Part 1 (Ch-30).
Epilogue.
Back to Linear Systems Part 2.
Back to Linear Systems Part 1.
Singular value decomposition - Part 2.
Singular value decomposition - Part 1.
Hermitian and Symmetric Matrices Part 4.
Hermitian and Symmetric Matrices Part 3.
Hermitian and Symmetric matrices Part 1.
Diagonalization Part 4.
Diagonalization Part 3.
Diaggonalization Part 2.
Diagonalization Part 1.
Inner Product and Orthogonality Part 6.
Inner product and orthogonality Part 5.
Inner Product and Orthogonality Part 4.
Inner Product and Orthogonality Part 3.
Inner Product and Orthogonality Part 2.
Inner product and Orthogonality part 1.
Linear transformations - part 5.
Linear transformations - part 4.
Linear transformations - part 3.
Linear transformations - part 2.
Basis Part 3.
Linear Transformations - part 1.
Basis Part 1.
Linear independence and subspaces part 4.
Linear independence and subspaces part 3.
Linear Independence and subspaces part 2.
Linear Independence and subspaces part 1.
vector spaces part -2.
Linear transformations - part 5.