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Linear Algebra @ SUNYIT (mat340/edmond), inspired by Prof. Strang's Linear Algebra 18.06 OCW lectures.

We solve Ax = b.             Applications: computational sciencelinear dynamical systemsrobotics and machine learning

Tasks and Homework:

8/30:
The Geometry of Linear Equations - row picture, column picture, matrix form.
Applications in Linear Dynamical Systems - can skip to 15:15; the beginning is funny but content free;  look for your favorite application
Ch. 8 Applications      -   skim and look for your favorite application
Ch 1. Intro to vectors    -  work through
1.1 Vectors and Linear Combinations        page8/1-13 (as always, those with answers at the back)
1.2 Lengths and Dot Products                   p19/1-13
1.3 Matrices                                            p29/1-4
2.1 Vectors and Linear Equations              p40/1-8

9/1:
2.1 continued                                        p40 / 12-30
2.2 The idea                                          p51 / 1-30
2.3 Elimination using matrices                p63 / 1-25
2.4 Algebra                                           p75 / 1-30
More Applications in LDS


9/6:
2.5 Inverse Matrices                           p89 / 1-30
2.6 Elimination = LU Factorization      p102 / 1-20

9/8:
2.7  Transposes, Permutations, PA=LU           p115 / 1-20
3.1  Vector Spaces                                        p127 / 1-30
LDS apps  - up to about 45:00; optionally, watch the rest to get a preview and a feel for applications of Ch.3

9/13:
Review for Test 1

9/15: 
Test 1

9/20:

9/22:
3.3  Rank and rref                                            p151 / 1-10
3.4  The Complete Solution to Ax = b                p163 / 1-30

9/27:
3.5  Independence, Basis and Dimension          p178 / 1-34
N(A) and C(A) - intuition and applications  (45:00 -> end)  - a bit advanced, so watch, sit back and relax; just get a feel for it and remember that this is actually very meaningful and useful.

9/29:
Watch Independence, Basis and Dimension for the second time and try to catch a small error
3.6  The cover of the book:   The Four Fundamental Subspaces           p190 / 1-20

10/4:
Skim Ch. 8 Applications, in particular 8.1 and 8.2.
8.2  Application: Graphs and Networks                p428 / 1-11

10/6:
Review for Applications (45:25 -> end) 

10/11:    Mini break:  Enjoy!!!

10/13:
4.1  Orthogonality of the Four Subspaces           p202 / 1-25
4.2  Projections                                               p214 / 1-20

10/18:
Great application:
4.3  Least Squares                                    p226 / 1-20           Application: Robotics
Review for Test 2

10/20:
Test 2

10/25:
4.4  Orthogonal Matrices and Gram-Schmidt            p239 / 1-20
A more applied look at Orthogonality (from 47:00 on), Fourier Series, Gram-Schmidt and QR  and  Least Squares

10/27:
5.1  Properties of Determinants                     p251 / 1-32
5.2  Determinant Formulas and Cofactors       p263 / 1-20
Optional:  Least Squares Applications - may give you ideas for a project

11/1:
5.3  Cramer's Rule and Volumes                    p279 / 1-20
6.1  Eigenvalues and Eigenvectors                 p293 / 1-30

11/3:
Catch up
Optional: Least norm solution (till 44:00)

11/8:
6.2  Diagonalizing a Matrix                             p307 / 1-20
6.3  Applications to Differential Equations         p325 / 1-25
Same topic, in engineering: Autonomous Linear Dynamical Systems  (from 44:00 on)

11/10:
Markov Matrices, steady state
6.4  Symmetric Matrices                              p337 / 1-20

11/15:
Review for Test 3

11/17:
Test 3

11/22:
6.5 Positive Definite Matrices                    p350 / 1-10
10.1 Complex Matrices                            p498 / 1-20

Thanksgiving

11/29:
6.7 Singular Value Decomposition (SVD)              p371 / 1-10

12/01:
7.1 Linear Transformations                                  p380 / 1-25

12/06:
7.3 Pseudoinverse                                             p406 / 1-10
Optional:     Ch. 8. Applications                            skim


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