Spring 2012:
Math 320 Section 001: Linear Algebra and Differential Equations
Schedule: MWF 9:55 – 10:45 AM. Van Vleck B 102
Syllabus: Can be found here
Textbook: Edwards and Penney, Differential Equations and Linear Algebra, third ed., Prentice Hall
Teaching assistants webpages for this course:
Sections 301, 302: Hesamaddin Dashti
Sections 303-306: Erkao Bao
Homework assignments:
Hw 1 Due Wednesday, February 1st. Solutions
Hw 2 Due Wednesday, February 8th. Solutions
Hw 3 Due Friday, February 17. Solutions
Hw4 Due Wednesday February 22. Solutions
Hw5 Due Friday March 2. Solutions
Hw6 Due Friday March 9. Solutions
Hw7 Due Friday March 16. Solutions
Hw8 Due Wednesday, March 21. Solutions
Hw9 Due Monday, March 26 Solutions
Hw10 Due Friday, April 13 Solutions
Hw11 Due Friday, April 20 Solutions
Hw12 Due Friday, April 27 Solutions
Hw13 Due Friday, May 4 Solutions
Hw 14 Optional
Practice Exam You can now find the solution HERE
Practice Exam 2 You can now find the solution HERE
Practice Exam 3 You can now find the solution HERE
Brief lecture outline:
Lecture 1: January 23
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Section 1.1 Differential equations and mathematical models
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Newton's law of cooling
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Population growth
Lecture 2: January 25
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Section 1.2: Integrals as general and particular solutions
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Second order Equations
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Velocity and acceleration
Lecture 3: January 27
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Section 1.3 Slope fields and solution curves
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Graphical method
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Existence and uniqueness of solutions
Lecture 4: January 30
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Section 1.4 Separable equations and applications
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Implicit, general and singular solutions
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Cooling and heating
Lecture 5: February 1
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Section 1.5 Linear first order equations
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Integrating factors
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Mixture problems
Lecture 6: February 3
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Section 1.6 Substitution methods and exact solutions
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Homogeneous equations
Lecture 7: February 6
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Bernoulli equations
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Exact differential equations
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Reducible second-order equations
Lecture 8: February 8
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Chapter 2: Mathematical Models and Numerical Analysis
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Section 2.1 Population models
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Bounded populations and the logistic equation
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Section 2.2 Equilibrium solutions and stability, autonomous equations
Lecture 9: February 10
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Logistic population with harvesting
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Bifurcation and dependance on parameters
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Section 2.4 Numerical approximation: Euler's method
Lecture 10: February 13
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Local and cumulative errors
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Section 2.5: A closer look at Euler's method
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Improved Euler's method
Lecture 11: February 15
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Chapter 3: Linear systems and matrices
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Section 3.1: Introduction to linear systems
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Two equations in two unknowns
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The method of elimination
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Three equations in three unknowns
Lecture 12: February 17
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Section 3.2: Matrices and Gaussian elimination
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Elementary row operations. Row equivalent matrices
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Gaussian elimination method
Lecture 13: February 20
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Echelon matrices
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Leading and free variables
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Section 3.3: Reduced row-echelon matrices
Lecture 14: February 22
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Gauss-Jordan elimination
Lecture 15: February 24: Exam 1
Lecture 16: February 27
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Homogeneous linear systems
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Section 3.4: Matrix operations
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Multiplication of matrices
Lecture 17: February 29
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Multiplication of matrices. Matrix algebra
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Section 3.5: Inverse of matrices.
Lecture 18: March 2
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Algorithm for finding A^{-1}
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Section 3.6 Determinants
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2x2 and nxn determinants
Lecture 19: March 5
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Row and column properties for determinants
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Cramer's rule for nxn systems
Lecture 20: March 7
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Chapter 4: Vector spaces
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Addition and multiplication by scalars
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Collinear vectors. Linear dependance
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Linear independence in R^3
Lecture 21: March 9
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Basis vectors in R^3
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Subspaces of R^3
Lecture 22: March 12
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Section 4.2: The vector space R^n and subspaces
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Addition and multiplication by scalars. Properties of vector spaces.
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The vector space of real valued functions
Lecture 23: March 14
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Subspaces
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Section 4.3: Linear combinations and independence of vectors
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Linear span
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Linear independence.
Lecture 24: March 16
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Section 4.4 Bases and dimension for vector spaces
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Basis
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Finite dimensional spaces
Lecture 25: March 19:
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Bases for solution spaces
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Algorithm for find a basis by elementary row operations
Lecture 26: March 21
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Section 4.5: Row and column space
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Row and column rank
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Extracting or completing bases
Lecture 27: March 23
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Chapter 5: Higher order linear differential equations
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Section 5.1 Intro: 2nd order linear equations
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Homogeneous equations
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A typical application
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Linear combinations: General solutions
Lecture 28: March 26
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Wronskians and linear independence
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Linear 2nd order equations with constant coefficients
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Case: Distinct roots
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Case: Repeated roots
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Section 5.2: General solutions of linear equations
Lecture 29: March 28
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Midterm 2
Lecture 30: March 30
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Non-homogeneous equations
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Particular and complementary solutions
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Section 5.3: Homogeneous equations with constant coefficients
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The characteristic equation
Lecture 31: April 09
1. Case: Distinct roots
2. Case: Repeated roots
Lecture 32: April 11
1. Case: Complex roots
2. Case: Repeated complex roots
Lecture 33: April 13
1. Section 5.4: Mechanical vibrations
2. Application: The simple pendulum
3. Free undamped motion
Lecture 34-36: April 16,18,20 (Covered by Uri Andrews) Sections 5.5, Section 5.6 (pages 353-357) and started 7.1
Lecture 37: April 23
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Chapter 7: Linear systems of differential equations
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Section 7.1: First order systems and applications
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Simple two dimensional systems
Lecture 38: April 25
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Section 7.2: Matrices and linear systems
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Homogeneous equations
Lecture 39: April 27
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Homogeneous equations
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Wronskians and linear independence
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General solutions
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Non-homogeneous solutions and the superposition principle
Lecture 40: April 30
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Section 7.3: The eigenvalue method for linear systems
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Eigenvalues and eigenvectors
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The characteristic polynomial
Lecture 41: May 2
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Eigenvalues, eigenvectors and linearly independent solutions
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The eigenvalue method
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Distinct real eigenvalues
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Complex eigenvalues (compartmental analysis has been excluded, as well as applications)
Lecture 42: May 4
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Section 7.5 Multiple eigenvalue solutions (section 7.4 has been excluded)
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Repeated eigenvalues, multiplicity
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Complete eigenvalues (defective eigenvalues have been excluded)
Lecture 43: May 7
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Chapter 8: Matrix exponential methods
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Section 8.1: Matrix exponentials and linear systems
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Fundamental matrices
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Solving initial value problems with the fundamental matrix
Lecture 44: May 9
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Matrix exponential solutions
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Initial value problems and the exponential solution
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How to compute the exponential of a matrix: for nilpotent matrices, using the fundamental matrix and by diagonalizing the matrix.
Lecture 45: May 11
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Examples: Computation of exponential matrices
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Review session
Discussion sessions:
Section |
Time |
Room Number |
Teaching Assistant |
|
301 |
T 8:50-9:40AM |
B119 Van Vleck Hall |
Hesamaddin Dashti |
dashti at math dot wisc dot edu |
302 |
R 8:50-9:40AM |
B119 Van Vleck Hall |
Hesamaddin Dashti |
dashti at math dot wisc dot edu |
303 |
T 11:00-11:50AM |
115 Ingraham Hall |
Erkao Bao |
bao at math dot wisc dot edu |
304 |
R 11:00-11:50AM |
115 Ingraham Hall |
Erkao Bao |
bao at math dot wisc dot edu |
305 |
T 9:55-10:45AM |
B329 Van Vleck Hall |
Erkao Bao |
bao at math dot wisc dot edu |
306 |
R 9:55-10:45AM |
B329 Van Vleck Hall |
Erkao Bao |
bao at math dot wisc dot edu |
Other important information:
Exam 1: February 24 Time: 9:55 - 10:45 AM. Room: Van Vleck B 102 20% of the Final Grade
Exam 2: March 28 Time: 9:55 - 10:45 AM. Room: Van Vleck B 102 25% of the Final Grade
Exam 3: May 13 Time: 7:45 – 9:45 AM. Room: Van Vleck B 102 30% of the Final Grade
*See the syllabus for more information on exam policies.
The TAs will grade a subset of the homework problems given out each week (with some points also given for completeness). The homework scores will count for 15% of the grade. The lowest homework score will be dropped.
There will be an estimate of 6 quizzes, to be scheduled during section meetings on dates to be determined by the TA. Quizzes will be graded and will count for 5% of the overall grade. The lowest quiz score will be dropped. There will be no make-up quizzes.
Class participation: 5 % of the final grade
Grading:
Exam 1: 20 %
Exam 2: 25 %
Exam 3: 30 %
Homework: 15%
Quizzes: 5%
Class participation: 5%
Note: Any student with a documented disability should contact me as soon as possible so that we can discuss arrangements to fit your needs.