Math 342 - Linear Algebra II - Fall 2019

Class Information

Instructor: Tuan Pham
TA: Matthias Merzenich
Section 20
Class meetings: Weniger Hall 149, MWF 2:00 - 2:50 PM
[Syllabus]   [Tentative calendar]   [Canvas site]

Office Hours

MWF 1:00 - 1:50 PM at Kidder Hall 268
MF 4:00 - 5:00 PM at Kidder Hall 268
W 4:00 - 5:00 PM at Kidder Hall 108 J (computer lab)

Assignments

Homework Solution (from TA) Recitation worksheets
Worksheet 1
Homework 1 Solution Worksheet 2
Homework 2 Solution Worksheet 3
Homework 3 Solution Worksheet 4
Homework 4 Solution Worksheet 5
Midterm review Worksheet 6
Homework 5 Solution Worksheet 7
Homework 6 Solution Worksheet 8
Homework 7 Solution Worksheet 9
Homework 8 Solution Worksheet 10
Final review Solution

Lecture notes

  • Lecture 27 (Dec. 4): normed vector space
  • Lecture 26 (Dec. 2): diagonalize a linear map; introduction of distance
  • Lecture 25 (Nov. 27): check if a linear map is diagonalizable
  • Lecture 24 (Nov. 25): find eigenvectors and eigenvalues
  • Lecture 23 (Nov. 22): diagonalizable linear maps, eigenvectors and eigenvalues
  • Lecture 22 (Nov. 20): introduction to spectral theory
  • Lecture 21 (Nov. 18): practice on direct sum and invariant subspaces
  • Lecture 20 (Nov. 15): checking if a sum is a direct sum
  • Lecture 19 (Nov. 13): direct sum of many subspaces; invariant subspaces
  • Lecture 18 (Nov. 8): direct sum
  • Lecture 17 (Nov. 6): find basis of vector space U + V
  • Lecture 16 (Nov. 4): summing two vector subspaces
  • Lecture 15 (Oct. 28): checking monomorphism, epimorphism, isomorphism
  • Lecture 14 (Oct. 25): connection between monomorphism, epimorphism, isomorphism and rank-nullity theorem
  • Lecture 13 (Oct. 23): monomorphism, epimorphism, isomorphism
  • Lecture 12 (Oct. 21): an application of rank-nullity theorem
  • Lecture 11 (Oct. 18): practice on null and range space, rank-nullity theorem
  • Lecture 10 (Oct. 16): operation on linear maps, null and range space
  • Lecture 9 (Oct. 14): computation of matrix representation
  • Lecture 8 (Oct. 11): linear maps, matrix representation
  • Lecture 7 (Oct. 9): linear maps, practice on writing proof
  • Lecture 6 (Oct. 7): basis and dimension
  • Lecture 5 (Oct. 4): linear independence
  • Lecture 4 (Oct. 2): subspace
  • Lecture 3 (Sep. 30): checking if a set is a vector space, practice on writing proof
  • Lecture 2 (Sep. 27): definition of vector spaces
  • Lecture 1 (Sep. 25): introduction

    • Remarks before / after class

  • Worksheet 12/06/2019
  • Worksheet 11/27/2019
  • Worksheet 11/18/2019
  • Worksheet 11/13/2019
  • Worksheet 11/06/2019
  • Solution to midterm exam
  • Worksheet 10/30/2019
  • Worksheet 10/28/2019
  • Worksheet 10/25/2019
  • For the topic of coordinate of a vector and matrix representation of a linear map, you can read Section 8 of Chapter 2 (starting on page 69). For the topic of monomorphism, epimorphism, isomorphism, you can read Section 3.B (from 3.12 to 3.24) in Axler's "Linear Algebra Done Right". The book doesn't use these terminologies, but use 'injective', 'surjective', 'bijective' instead. However, the terms 'monomorphism', 'epimorphism', 'isomorphism' are quite standard in the context of linear maps.
  • Worksheet 10/18/2019
  • Worksheet 10/14/2019
  • Worksheet 10/11/2019
  • Worksheet 10/9/2019
  • Worksheet 10/4/2019
  • Worksheet 9/30/2019
  • Instructions to install Matlab

    • Links

    Department of Mathematics
    Oregon State University
    This page was last modified on Tuesday, December 10, 2019.