Math 341 - Linear Algebra I - Fall 2018

Class Information

Instructor: Tuan Pham
Grader: Chifan Leung
Section 10
Class meetings: Bexell Hall 207, MWF 2:00 - 2:50 PM
[Syllabus]   [Tentative calendar]   [Canvas site]

Office Hours

MW 3:00 - 3:50 PM, Friday 1:00 - 1:50 PM at Kidder Hall 268
Friday 3:00 - 4:00 PM at Kidder Hall 108J (computer lab).

Assignments

Homework Solution to selected HW problems (see Chifan's comments in Canvas) Quizzes Labs
Homework 1 Solution Quiz 1 Lab 0
Homework 2 Solution Quiz 2 Lab 1
Homework 3 Solution Quiz 3 Lab 2
Homework 4 Solution Quiz 4 Lab 3
Homework 5 Solution Quiz 5 Lab 4
Homework 6 Solution Quiz 6
Homework 7 Solution Quiz 7
Homework 8 Solution
Homework 9 Solution

Lecture notes

  • Lecture 26 (Nov. 26): applications of matrix diagonalization: system of differential equations.
  • Lecture 25 (Nov. 21): applications of matrix diagonalization: power of matrix, recursive sequence.
  • Lecture 24 (Nov. 19): matrix diagonalization, complex eigenvalues.
  • Lecture 23 (Nov. 16): matrix diagonalization, general procedure.
  • Lecture 22 (Nov. 14): matrix diagonalization and geometric description.
  • Lecture 21 (Nov. 9): eigenvalues and eigenvectors.
  • Lecture 20 (Nov. 7): matrix representation of a linear map in different bases.
  • Lecture 19 (Nov. 5): compute kernel and range; relationship of row, column, null spaces; coordinates of vectors.
  • Lecture 18 (Nov. 2): range of linear maps, rank-nullity theorem.
  • Lecture 17 (Oct. 31): algebra and kernel of linear maps.
  • Lecture 16 (Oct. 29): rank-nullity theorem, matrix representation of linear map.
  • Lecture 15 (Oct. 24): basis of null space.
  • Lecture 14 (Oct. 22): basis of span of vectors, column space, row space.
  • Lecture 13 (Oct. 19): basis of a subspace.
  • Lecture 12 (Oct. 17): checking for linear independence and linear combination.
  • Lecture 11 (Oct. 15): subspace, span, linear combination, linear dependence.
  • Lecture 10 (Oct. 12): determinant, computation and basket-weave method.
  • Lecture 9 (Oct. 10): determinant, product rule.
  • Lecture 8 (Oct. 8): determinant, motivation and basic properties.
  • Lecture 2 (Sep. 24): system of linear equations, row echelon form of a matrix.
  • Lecture 1 (Sep. 21): Introduction to Linear Algebra.

    • Remarks before / after class

  • Worksheets 11/30/2018
  • Some review problems for Final
  • Worksheets 11/28/2018
  • Worksheets 11/26/2018
  • Solutions to midterm exam
  • Supporting files for Lab 3: char2num.m, num2char.m, string2pairs.m, pairs2string.m
  • Some review problems for Midterm.
  • 10/10/2018: In Problem 5, the phrase "inverse image" is equivalent to "pre-image". R is the region of all pre-images of points in the square S. You simply compute the pre-image of each vertex of the square, then connect these points together. In Problem 6, you can use the following property which I haven't mentioned in class: the determinant of an upper triangular matrix is equal to the product of the entries on the diagonal. An upper triangular matrix is a matrix whose every entry below the diagonal is equal zero.
  • 10/3/2018: You can read Section 7.3 in the textbook for an example of finding inverse matrix by Gauss-Jordan elimination method. You will need the following rule for the last problem of HW 2: a matrix is invertible if and only if its RREF is exactly the identity matrix. We will discuss this in more detail on Friday.
  • Worksheets 9/26/2018
  • Worksheets 9/24/2018
  • Prepare for class on Sep 26: read Chap. 5 and 6.
  • Prepare for class on Sep 24: read Chap. 2 and Sec. 4.2.

    • Links

    Department of Mathematics
    Oregon State University
    This page was last modified on Saturday, December 1, 2018