Complex eigenvalues are associated with circular and cyclical motion. Introduction to Eigenvalues 285 Multiplying by A gives . •However,adynamic systemproblemsuchas Ax =λx … v; Where v is an n-by-1 non-zero vector and λ is a scalar factor. An eigenvector of A is a nonzero vector v in R n such that Av = λ v, for some scalar λ. (λI −A)v = 0, i.e., Av = λv any such v is called an eigenvector of A (associated with eigenvalue λ) • there exists nonzero w ∈ Cn s.t. Now, if A is invertible, then A has no zero eigenvalues, and the following calculations are justified: so λ −1 is an eigenvalue of A −1 with corresponding eigenvector x. then λ is called an eigenvalue of A and x is called an eigenvector corresponding to the eigen-value λ. Proof. If V is finite dimensional, elementary linear algebra shows that there are several equivalent definitions of an eigenvalue: (2) The linear mapping. Properties on Eigenvalues. 1 λ is an =⇒ eigenvalue of A−1 A is invertible ⇐⇒ det A =0 ⇐⇒ 0 is not an eigenvalue of A eigenvectors are the same as those associated with λ for A facts about eigenvaluesIncredible. 4. If λ \lambda λ is an eigenvalue for A A A, then there is a vector v ∈ R n v \in \mathbb{R}^n v ∈ R n such that A v = λ v Av = \lambda v A v = λ v. Rearranging this equation shows that (A − λ ⋅ I) v = 0 (A - \lambda \cdot I)v = 0 (A − λ ⋅ I) v = 0, where I I I denotes the n n n-by-n n n identity matrix. So λ 1 +λ 2 =0,andλ 1λ 2 =1. In fact, together with the zero vector 0, the set of all eigenvectors corresponding to a given eigenvalue λ will form a subspace. Eigenvectors and eigenvalues λ ∈ C is an eigenvalue of A ∈ Cn×n if X(λ) = det(λI −A) = 0 equivalent to: • there exists nonzero v ∈ Cn s.t. This ends up being a cubic equation, but just looking at it here we see one of the roots is 2 (because of 2−λ), and the part inside the square brackets is Quadratic, with roots of −1 and 8. detQ(A,λ)has degree less than or equal to mnand degQ(A,λ)

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