Im trying to figure out how to solve this in matlab, and the other questions that show this are either handwritten solut
Posted: Thu May 12, 2022 3:40 pm
Im trying to figure out how to solve this in matlab, and the
other questions that show this are either handwritten solutions or
completely off, if someone could help with this I would greatly
appreciate it
8. Consider the predator-prey model S X(4 – 3y) dy di = y(x - 2) dac dt in which x > 0 represents the population of the prey and y > 0 represents the population of the predators. (a) Find all critical points of the system. At each critical point, calculate the corre- sponding linear system and find the eigenvalues of the coefficient matrix; then identify the type and stability of the critical point. (b) Plot the vector field on a region small enough to distinguish the critical points but large enough to judge the possible solution behaviors away from the critical points. (c) Use several initial data points (xo, Yo) in the first quadrant to draw a phase por- trait for the system. Identify the direction of increasing t on the trajectories you obtain. Use the information from parts (a) and (b) to choose a representative sample of initial conditions. Then combine the vector field and phase portrait on a single graph. (d) Explain from your phase portrait how the populations vary over time for initial data close to the unique critical point inside the first quadrant. What happens for initial data far from this critical point? (e) Suppose the initial state of the population is given by x(0) = 1, y(0) = 1. = Find the state of the population at t = 1, 2, 3, 4, 5. (f) Estimate to two decimal places the period of the solution curve that starts at (1,1).
other questions that show this are either handwritten solutions or
completely off, if someone could help with this I would greatly
appreciate it
8. Consider the predator-prey model S X(4 – 3y) dy di = y(x - 2) dac dt in which x > 0 represents the population of the prey and y > 0 represents the population of the predators. (a) Find all critical points of the system. At each critical point, calculate the corre- sponding linear system and find the eigenvalues of the coefficient matrix; then identify the type and stability of the critical point. (b) Plot the vector field on a region small enough to distinguish the critical points but large enough to judge the possible solution behaviors away from the critical points. (c) Use several initial data points (xo, Yo) in the first quadrant to draw a phase por- trait for the system. Identify the direction of increasing t on the trajectories you obtain. Use the information from parts (a) and (b) to choose a representative sample of initial conditions. Then combine the vector field and phase portrait on a single graph. (d) Explain from your phase portrait how the populations vary over time for initial data close to the unique critical point inside the first quadrant. What happens for initial data far from this critical point? (e) Suppose the initial state of the population is given by x(0) = 1, y(0) = 1. = Find the state of the population at t = 1, 2, 3, 4, 5. (f) Estimate to two decimal places the period of the solution curve that starts at (1,1).