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  2. Linear stability - Wikipedia

    en.wikipedia.org/wiki/Linear_stability

    According to Vakhitov–Kolokolov stability criterion, [5] when k > 2, the spectrum of A has positive point eigenvalues, so that the linearized equation is linearly (exponentially) unstable; for 0 < k ≤ 2, the spectrum of A is purely imaginary, so that the corresponding solitary waves are linearly stable.

  3. Stability theory - Wikipedia

    en.wikipedia.org/wiki/Stability_theory

    If there exists an eigenvalue λ of A with Re(λ) > 0 then the solution is unstable for t → ∞. Application of this result in practice, in order to decide the stability of the origin for a linear system, is facilitated by the Routh–Hurwitz stability criterion. The eigenvalues of a matrix are the roots of its characteristic polynomial.

  4. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    The corresponding eigenvalue, ... for example in stability ... is itself a function of its associated eigenvalue. In particular, for λ = 0 the ...

  5. Hurwitz-stable matrix - Wikipedia

    en.wikipedia.org/wiki/Hurwitz-stable_matrix

    The Hurwitz stability matrix is a crucial part of control theory. A system is stable if its control matrix is a Hurwitz matrix. The negative real components of the eigenvalues of the matrix represent negative feedback. Similarly, a system is inherently unstable if any of the eigenvalues have positive real components, representing positive feedback.

  6. Eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Eigenvalue_algorithm

    Given an n × n square matrix A of real or complex numbers, an eigenvalue λ and its associated generalized eigenvector v are a pair obeying the relation [1] =,where v is a nonzero n × 1 column vector, I is the n × n identity matrix, k is a positive integer, and both λ and v are allowed to be complex even when A is real.l When k = 1, the vector is called simply an eigenvector, and the pair ...

  7. Jacobian matrix and determinant - Wikipedia

    en.wikipedia.org/wiki/Jacobian_matrix_and...

    Specifically, if the eigenvalues all have real parts that are negative, then the system is stable near the stationary point. If any eigenvalue has a real part that is positive, then the point is unstable. If the largest real part of the eigenvalues is zero, the Jacobian matrix does not allow for an evaluation of the stability. [12]

  8. Orr–Sommerfeld equation - Wikipedia

    en.wikipedia.org/wiki/Orr–Sommerfeld_equation

    The Orr–Sommerfeld equation, in fluid dynamics, is an eigenvalue equation describing the linear two-dimensional modes of disturbance to a viscous parallel flow. The solution to the Navier–Stokes equations for a parallel, laminar flow can become unstable if certain conditions on the flow are satisfied, and the Orr–Sommerfeld equation determines precisely what the conditions for ...

  9. Linear dynamical system - Wikipedia

    en.wikipedia.org/wiki/Linear_dynamical_system

    Thus if < then the eigenvalues are of opposite sign, and the fixed point is a saddle. If Δ > 0 {\displaystyle \Delta >0} then the eigenvalues are of the same sign. Therefore, if τ > 0 {\displaystyle \tau >0} both are positive and the point is unstable, and if τ < 0 {\displaystyle \tau <0} then both are negative and the point is stable.