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Linear Systems with Constant Coefficients

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Part of the book series: Texts in Applied Mathematics ((TAM,volume 65))

Abstract

The bulk of this chapter is devoted to homogeneous linear systems of ODEs with real constant coefficients. This means systems of the form

$$\displaystyle{ \begin{array}{ccc} x_{1}^{{\prime}}& =& a_{11}x_{1} + a_{12}x_{2} +\ldots +a_{1d}x_{d}, \\ x_{2}^{{\prime}}& =& a_{21}x_{1} + a_{22}x_{2} +\ldots +a_{2d}x_{d},\\ \\ \vdots&\vdots&\vdots\\ \\ x_{d}^{{\prime}}& =&a_{d1}x_{1} + a_{d2}x_{2} +\ldots +a_{dd}x_{d}.\end{array} }$$
(2.1)

(From now on, we shall let d be the dimension of our systems, so that the index n is available for other uses.) The written-out system (2.1) is awkward to read or write, and we shall normally use the vastly more compact linear-algebra notation

$$\displaystyle{ \mathbf{x}^{{\prime}} = A\mathbf{x}, }$$
(2.2)

where x = (x 1, x 2, , x d ) is a d-dimensional vector of unknown functions, A is a d × d matrix with real entries, and matrix multiplication is understood in writing A x. In vector notation, an appropriate initial condition for (2.2) is

$$\displaystyle{ \mathbf{x}(0) = \mathbf{b}, }$$
(2.3)

where \(\mathbf{b} \in \mathbb{R}^{d}\).

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Notes

  1. 1.

    The two factors on the RHS of (2.4) must be written in the order in which they appear.

  2. 2.

    The vector space need not be finite-dimensional. Indeed, in the next chapter, we shall encounter a norm on an infinite-dimensional space.

  3. 3.

    Up to this point, it does not matter whether we consider the basic equation expressing similarity to be B = S −1 AS or B = SAS −1 . Here, however, there is a difference: the columns of the matrix S such that S −1 AS is diagonal are the eigenvectors of A, while the characterization of S −1 is less transparent.

  4. 4.

    Recall that a square matrix N is called nilpotent if there exists a positive integer k such that N k = 0.

  5. 5.

    Although the minimal polynomial is useful in proving that transformation to the Jordan form is possible, it is a distraction in calculating the Jordan form.

  6. 6.

    In Chapter 6, we will extend this classification to equilibria of nonlinear systems.

  7. 7.

    Note that the integrand in (2.51) is vector-valued. Such an integral can be interpreted componentwise, giving a collection of ordinary, scalar, integrals.

  8. 8.

    The introduction of polar coordinates represents a nonlinear change of coordinates in an ODE. Linear changes of coordinates were exploited in Section 2.3.

  9. 9.

    In the case of simple eigenvalues, this result is easily proved with the implicit function theorem. Multiple eigenvalues raise more subtle issues that we ignore here, but continuous dependence, appropriately interpreted, still holds. (Cf. Section C.3 of Appendix C.)

  10. 10.

    For your information, with a little extra work, it is possible to construct a \(\mathcal{C}^{\infty }\) function that equals zero for t ≤ 0 and equals unity for t ≥ 1. See [73], pp. 48–50.

  11. 11.

    We regard this terminology as unfortunate, since the word hyperbolic already has so many uses in mathematics, but it is well established and we adopt it. The term “hyperbolic” derives from the simplest system with such a coefficient matrix,

    $$\displaystyle{\left [\begin{array}{c} x^{{\prime}} \\ y^{{\prime}} \end{array} \right ] = \left [\begin{array}{cc} 0 & 1\\ 1 & 0 \end{array} \right ]\left [\begin{array}{c} x\\ y \end{array} \right ],}$$

    whose solutions move along hyperbolas {x 2y 2 = C} where C is a constant. In general, however, orbits for hyperbolic systems have at best only a qualitative resemblance to hyperbolas, and possibly none at all.

References

  1. M. W. Hirsch and S. Smale, Differential equations, dynamical systems, and linear algebra, Academic Press, New York, 1974.

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  2. W. Rudin, Principles of mathematical analysis, 3rd edition., McGraw-Hill, New York, 1976.

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  3. R. Shakarchi, Problems and solutions for undergraduate analysis, Springer, New York, 1998.

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  4. G. Strang, Linear algebra and its applications, 4th edition, Cengage, 2006.

    Google Scholar 

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Schaeffer, D.G., Cain, J.W. (2016). Linear Systems with Constant Coefficients. In: Ordinary Differential Equations: Basics and Beyond. Texts in Applied Mathematics, vol 65. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6389-8_2

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