Partially decoupled linear system

In summary: I read the problem as asking for some solutions that lie on straight lines, not for all solutions. I do agree with HallsofIvy that y = mx is the way to solve this, and that m is an eigenvalue.
  • #1
hover
343
0

Homework Statement



x' = x-3y
y'= -2y

There are two solutions of this system that lie on straight lines, in the sense
that the ratio y(t)/x(t) is constant along each such solution. Find these lines and the
corresponding solutions.

Homework Equations



None in particular that I can think of


The Attempt at a Solution



I don't follow the question. I see that it asks for 2 particular solutions that are straight lines but how does y(t)/x(t) come into this to help me solve for them?

thanks
 
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  • #2
hover said:

Homework Statement



x' = x-3y
y'= -2y

There are two solutions of this system that lie on straight lines, in the sense
that the ratio y(t)/x(t) is constant along each such solution. Find these lines and the
corresponding solutions.

Homework Equations



None in particular that I can think of


The Attempt at a Solution



I don't follow the question. I see that it asks for 2 particular solutions that are straight lines but how does y(t)/x(t) come into this to help me solve for them?

thanks
I believe that where they're going with this problem is looking at the solutions if x' = 0 or y' = 0. Substitute 0 for x' and y' and you'll see that the solutions are straight lines, and the ratio y(t)/x(t) will make more sense.
 
  • #3
I'm afraid (and amazed) that Mark44 is mistaken here (or I am misunderstanding him- more likely that). You are NOT looking for "equilibrium solutions" (where x'= 0 and y'= 0). The only equilibrium solution is (0, 0). What you are looking for are straight line solutions through (0, 0).

If y= mx, then y'= mx'. Since y'= x- 3y and y'= -2y, that says that -2y= m(x- 3y). but y= mx so that is -2mx= m(x- 3mx)= m(1- 3)x. Since that is to be true for all x, -2m= m(1- 3m). Can you solve that equation for m? What lines does that give you?

(The values of m, by the way, will be eigenvalues of the coefficient matrix,
[tex]\begin{bmatrix}1 & -3 \\ 0 & -2\end{bmatrix}[/tex]
and the lines are in the direction of the eigenvectors.)
 
Last edited by a moderator:
  • #4
HallsofIvy said:
I'm afraid (and amazed) that Mark44 is mistaken here (or I am misunderstanding him- more likely that).
It can happen that I am mistaken. :blushing:
 

1. What is a partially decoupled linear system?

A partially decoupled linear system is a mathematical model that represents a set of linear equations where some variables are dependent on others, but not all variables are dependent on each other. This means that the system can be simplified into smaller, independent subsystems for analysis and solution.

2. How is a partially decoupled linear system different from a fully coupled linear system?

A fully coupled linear system is one where all variables are dependent on each other, making it more complex and difficult to solve. In contrast, a partially decoupled linear system has some variables that are independent and can be solved separately, making it easier to analyze and solve.

3. What are the advantages of using a partially decoupled linear system?

One advantage of using a partially decoupled linear system is that it reduces the complexity of the overall system, making it easier to analyze and understand. It also allows for efficient and accurate solutions to be obtained for each subsystem, which can then be combined to find the overall solution.

4. What types of problems can be modeled using a partially decoupled linear system?

Partially decoupled linear systems are commonly used in various fields such as engineering, physics, and economics. They can be used to model systems with multiple interconnected components, such as electrical circuits, chemical reactions, and economic systems.

5. What methods are used to solve a partially decoupled linear system?

There are several methods that can be used to solve a partially decoupled linear system, including Gaussian elimination, matrix inversion, and iterative methods like Jacobi or Gauss-Seidel. The choice of method depends on the size and complexity of the system, as well as the desired level of accuracy.

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