This course gives an elementary treatment of linear algebra and its applications that are suitable for freshman. The aim is to present the fundamentals of linear algebra and its applications in the clearest possible way-pedagogy is the main consideration. Most of the need-to-know concepts in basic linear algebra will be covered in this course, which include the notion of systems of linear equations, vector spaces, linear transformations, and matrix theory.
學習目標:
1. Solve simple linear equations when there exists a solution for the system Ax=bS.
2. Conceptualize the 4 fundamental subspaces and grasp the idea of independence.
3. Compute the determinants using various techniques such as co-factor and property
4. Find eigenveluaes, and realize diagonalization
教科書:
Anton Rorres, elementary linear algebra with supplemental applications. 12th Ed., Wiley, 2019.
課程大綱
分配時數
核心能力
備註
單元主題
內容綱要
講授
示範
隨堂作業
其他
Systems of Linear Equations & Matrices
Linear Equations, Gaussian Elimination, Matrices and Matrix Operation, Inverse: Algebraic Properties of Matrices,Elementary Matrices, Invertible
6
1.5
1.11.21.32.12.23.13.24.14.24.34.4
Determinants
Cofactor Expansion, Cramer's Rule
6
1.5
1.11.21.32.12.23.13.24.14.24.34.4
General Vector Space
Vector Space, Subspace, Linearly Independent/Dependent, Basis, Dimension, Row Space, Column Space and Null Space, Rank, Matrix Transformation, Geometry of Matrix Operator
12
1.5
1.11.21.32.12.23.13.24.14.24.34.4
Eigenvalues and Eigenvectors
Eigenveluaes, Diagonalization
6
1.5
1.11.21.32.12.23.13.24.14.24.34.4
Inner Product Spaces
Inner Product Spaces, Orthogonality, Gram-Schmidt Process
The contents would be applied to other Engineering Mathematics. Furthermore, the major concepts about Vector spaces, Eigenvalues, and Eigenvectors are the fundamentals of Communications /Electrical Engineering.
達成指標:
Solve the problem of linear system
評量工具(可複選):
Quiz, Midterm and Final test
2.1
培養分析問題的能力。()
為何有關:
Model a system with linear properties.
達成指標:
Know the skill to formulate linear equations and find corresponding characteristics (determinant, eigenvalue, ...)