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which is the characteristic equation of the recurrence relation. Solve for to obtain the two roots , : these roots are known as the characteristic roots or eigenvalues of the characteristic equation. Different solutions are obtained depending on the nature of the roots: If these roots are distinct, we have the general solution
If the characteristic equation has a root r 1 that is repeated k times, then it is clear that y p (x) = c 1 e r 1 x is at least one solution. [1] However, this solution lacks linearly independent solutions from the other k − 1 roots. Since r 1 has multiplicity k, the differential equation can be factored into [1]
Costate equations — equation for the "Lagrange multipliers" in Pontryagin's minimum principle; Hamiltonian (control theory) — minimum principle says that this function should be minimized; Types of problems: Linear-quadratic regulator — system dynamics is a linear differential equation, objective is quadratic
The corresponding eigenvalue, characteristic value, or characteristic root is the multiplying factor (possibly negative). Geometrically, vectors are multi-dimensional quantities with magnitude and direction, often pictured as arrows. A linear transformation rotates, stretches, or shears the vectors upon which it acts. Its eigenvectors are those ...
Example: consider the following differential equation (Kummer's equation with a = 1 and b = 2): ″ + ′ = The roots of the indicial equation are −1 and 0. Two independent solutions are 1 / z {\displaystyle 1/z} and e z / z , {\displaystyle e^{z}/z,} so we see that the logarithm does not appear in any solution.
As an example, consider the advection equation (this example assumes familiarity with PDE notation, and solutions to basic ODEs). + = where is constant and is a function of and . We want to transform this linear first-order PDE into an ODE along the appropriate curve; i.e. something of the form
We call p(λ) the characteristic polynomial, and the equation, called the characteristic equation, is an N th-order polynomial equation in the unknown λ. This equation will have N λ distinct solutions, where 1 ≤ N λ ≤ N. The set of solutions, that is, the eigenvalues, is called the spectrum of A. [1] [2] [3]
The polynomial x 2 + 1 = 0 has roots ± i. Any real square matrix of odd degree has at least one real eigenvalue. For example, if the matrix is orthogonal, then 1 or −1 is an eigenvalue. The polynomial + has roots , +,, and thus can be factored as