| Week 1 |
- Basic definitions. Qualitative and Quantitative approaches.
- Initial Value Problems. First order linear equations.
- Method of Integrating factor.
- Method of Variation of Parameters.
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- Integrating factor and first order linear equations (review).
- Separable equations. Lots of exercises.
- Modeling with first order equations. Mixing problem.
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- Quiz 1.
- Remarks on direction fields.
- Existence and uniqueness of solutions to initial value problems. Proof for the linear case.
- Differences between linear and nonlinear first order differential equations.
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| Week 2 |
- Autonomous equations. Interval of definition of a solution. Direction fields.
- Population models. Stable and unstable equilibrium solutions.
- Exact first order differential equations.
- Integrating factors.
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- Numerical approximations. Euler's method.
- First order difference equations. Stable, asymptotic stable, semistable and unstable equilibrium.
- Stairstep diagrams (spider's web diagrams)
- Discussion session on homework problems.
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- Second order equations. Linear equations.
- Homogeneous equations with constant coefficients.
- Characteristic equation. Positive, negative and zero discriminant cases. Several examples.
- Quiz 2.
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| Week 3 |
- Quick review of Linear Algebra. Vector space, linear combination, linear independence.
- Span of a set, basis of a vector space, dimension, linear transformations.
- The above concepts in the setting of second order linear homogeneous differential equations.
- Review for the midterm.
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- The Wronskian.
- Fundamental set of solutions.
- Nonhomogeneous second order linear differential equations. Undetermined coefficients.
- Variation of parameters (just mentioned). To be fully covered later when studying systems of
first order linear differential equations.
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| Week 4 |
- General theory of higher order linear equations.
- Homogeneous equations with constant coefficients.
- The method of undetermined coefficients.
- Quiz 3.
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- Review of Matrices. Matrix functions.
- Eigenvalues and eigenvectors.
- Linear systems (dimension 2).
- The matrix etAc as the general solution to the
homogeneous system x'=Ax.
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- Linear systems. Homogeneous systems x'=A(t)x . Wronskian. Fundamental Matrix.
- Nonhomogeneous linear systems x'=A(t)x+g(t). Variation of Parameters method.
- Autonomous homogeneous linear systems x'=Ax. The matrix etA
for different matrices A.
- Quiz 4.
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| Week 5 |
- The autonomous system x'=Ax with A in
Mn×n with constant real entries.
- The system X'=AX vs. x'=Ax. A fundamental matrix of X'=AX constructed with n
linearly independent
eigenvectors of A.
- Homogeneous linear systems of dimension two. Phase portraits.
- Classification of solutions to x'=Ax according to the
sign of the discriminant tr2(A)-det(A).
Case 1: det(A) not equal to zero. Case 2: det(A)=0.
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- Summary of classification of solutions of two dimensional linear homogeneous systems x'=Ax.
- Bifurcation points.
- Nonlinear homogeneous linear systems x'=v(x) (v(x) is a vector field different from Ax).
Example: Predatory-prey model. Phase portrait analysis.
- Review of nonhomogeneous linear systems x'=Ax+g(t). Variation of parameters.
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- Review
- Final due: Fr, Aug 29
- Students evaluations.
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