3. Suppose Un+1= A Un is a matrix difference equation which describes discreet population changes from year to year A. Suppose matrix A has eigenvalues X1 and d2 with corresponding eigenvectors V and W. What is the general solution of this difference equation ?
3. Suppose Un+1= A Un is a matrix difference equation which describes discreet population changes from year to year A. Suppose matrix A has eigenvalues X1 and d2 with corresponding eigenvectors V and W. What is the general solution of this difference equation ?
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
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
Transcribed Image Text:### Matrix Difference Equations in Population Dynamics
3. Suppose \( U_{n+1} = A U_n \) is a **matrix difference** equation which describes discrete population changes from year to year.
**A.** Suppose matrix \( A \) has eigenvalues \( \lambda_1 \) and \( \lambda_2 \) with corresponding eigenvectors \( V \) and \( W \).
What is the general solution of this difference equation?
**B.** Let \( U_N = \begin{pmatrix} x_N \\ y_N \end{pmatrix} \) where \( x \) represents the number of individuals in the first stage of life and \( y \) represents the number of individuals in the second stage of life in this population.
In the long run, how do you find the fraction of the population that will be in stage one and the fraction of the population that will be in stage two?
In analyzing population dynamics using matrix difference equations, it is essential to understand the components involved in the equations, such as eigenvalues, eigenvectors, and how to interpret them for long-term predictions.
If you have any questions or need further explanations, please feel free to ask!
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