2. Order Linear Inhomogenous Recurrence Relations with Constant Coefficients

In summary: The converse I gave before (the difference of two solutions is a solution of the homogeneous equation) is true- but not very useful! The point is, if you know one solution to the inhomogeneous equation, g, then you can find all solutions to the inhomogeneous equation by adding that solution to all solutions to the homogeneous equation- exactly as you said. But that doesn't help you find g. To do that, you need to use some other method (which depends on what f is). In the first place, I was just trying to explain why, given any particular g, V+g will be a solution to the inhomogeneous equation. The other point is that if you can find one
  • #1
e(ho0n3
1,357
0
I need to show that the solution of

[tex]a_n = c_1a_{n-1} + c_2a_{n-2} + f(n)[/tex] (1)

is of the form

[tex]U_n = V_n + g(n)[/tex] (2)

where [itex]V_n[/itex] is the solution of a 2. order linear homogenous recurrence relation with constant coefficients.

Could I use the argument that if (2) is a solution to (1), then there are constants b and d such that [itex]bU_{n-1} + dU_{n-2}[/itex] is also a solution to (1)? This is the only thing I can think of (and am familiar with since the book uses this argument in two proofs). I don't know anything about generating functions so I don't know what to do.
 
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  • #2
Write your equation as:
[tex]a_{n}-c_{1}a_{n-1}-c_{2}a_{n-2}=f(n) (1)[/tex]

Assume g(n) is a solution of (1)

Let U(n) be another solution of (1)

Let V(n) be the difference, V(n)=U(n)-g(n)
Then we have:
[tex]V_{n}-c_{1}V_{n-1}-c_{2}V_{n-2}=U_{n}-c_{1}U_{n-1}-c_{2}U_{n-2}-(g_{n}-c_{1}g_{n-1}-c_{2}g_{n-2})=[/tex]
[tex]f(n)-f(n)=0[/tex]

That is, V(n) is a solution of the associated homogenous recurrence relation.
 
  • #3
arildno said:
Write your equation as:
[tex]a_{n}-c_{1}a_{n-1}-c_{2}a_{n-2}=f(n) (1)[/tex]

Assume g(n) is a solution of (1)

Let U(n) be another solution of (1)

Let V(n) be the difference, V(n)=U(n)-g(n)
Then we have:
[tex]V_{n}-c_{1}V_{n-1}-c_{2}V_{n-2}=U_{n}-c_{1}U_{n-1}-c_{2}U_{n-2}-(g_{n}-c_{1}g_{n-1}-c_{2}g_{n-2})=[/tex]
[tex]f(n)-f(n)=0[/tex]

That is, V(n) is a solution of the associated homogenous recurrence relation.
Interesting. I'm not convinced though since you had to assume g(n) is a solution to (1). If it isn't, then what?
 
  • #4
e(ho0n3 said:
Interesting. I'm not convinced though since you had to assume g(n) is a solution to (1). If it isn't, then what?

That was an (unmentioned) condition of the original problem: if Vn is a solution to the corresponding homogeneous equation then Vn+ g(n) is a solution to the inhomgeneous equation if and only if g(n) is a particular solution to the inhomogeneous equation.

To answer the poster's original question: "Could I use the argument that if (2) is a solution to (1), then there are constants b and d such that [itex]bU_{n-1} + dU_{n-2}[/itex] is also a solution to (1)?", No, you can't because it is not true: Pluginging [itex]bU_{n-1} + dU_{n-2}[/itex] into the equation would give (b+d)f(n), not f(n). A linear combination of solutions is a solution only for homogeneous equations.
 
  • #5
HallsofIvy said:
That was an (unmentioned) condition of the original problem: if Vn is a solution to the corresponding homogeneous equation then Vn+ g(n) is a solution to the inhomgeneous equation if and only if g(n) is a particular solution to the inhomogeneous equation.
I really wish I had the ability to figure this stuff out, like you seem to do. I still don't follow they line of logic being employed to determine that g(n) must be a solution in order for Vn+ g(n) to be a solution and vice versa.

To answer the poster's original question: "Could I use the argument that if (2) is a solution to (1), then there are constants b and d such that [itex]bU_{n-1} + dU_{n-2}[/itex] is also a solution to (1)?", No, you can't because it is not true: Pluginging [itex]bU_{n-1} + dU_{n-2}[/itex] into the equation would give (b+d)f(n), not f(n).
I came to this conclusion as well, but I wasn't really sure so I decided to post the problem here.
 
  • #6
Suppose V(n) is a solution of the hom. equation.
Assume that V(n)+g(n) is a solution of the inhom. equation.

Then it follows that g(n) itself is a solution of the inhom. solution.

The converse:
Assume that g(n) is a solution of the inhom. equation.

It then follows that V(n)+g(n) is a solution of the inhom. equation.
 
  • #7
To expand on what arildno just said: Suppose A(xn) is some linear recurrance relation- that is A(xn)= axn+2+ bxn+1+cxn, etc. A "homogeneous" equation is of the form A(xn)= 0. It's
easy to show that any linear combination of solutions is still a solution: If Vn and Un are satisfy A(Un)= 0 and A(Vn)= 0 then A(pUn+ qVn)= 0 also for any number p and q. "Second order" or "constant coefficients" are not needed but "linear" is. You simply use the definition of A (or more generally the definition of "linear") to show that A(pUn+qVn)= p A(Un)+ q A(Vn)= p(0)+ q(0)= 0.

Now, suppose Rn and Sn are both solutions to the non-homogeneous equation A()= f(n)- that is, that A(Rn)= f(n) and A(Sn)= f(n). Again, using the fact that A is linear, A(Rn- Sn)= A(Rn)- A(Sn)= f(n)- f(n)= 0.

That is, the difference between Rn and Sn satisfies the homogeneous equation: Rn- Sn= Un for some U satisfying the homogeneous equation. That is the same as saying Rn= Un+ Sn.

The exact same this is true, incidently, for homogenous and non-homogeneous differential equations.
 
  • #8
arildno said:
Suppose V(n) is a solution of the hom. equation.
Assume that V(n)+g(n) is a solution of the inhom. equation.

Then it follows that g(n) itself is a solution of the inhom. solution.

The converse:
Assume that g(n) is a solution of the inhom. equation.

It then follows that V(n)+g(n) is a solution of the inhom. equation.
I still don't see how the consequent follows from the antecedent. Here is my reasoning on why g(n) must be assumed to be a solution of the inhom. equation so that Vn + g(n) is a solution:

We know that [itex]V_n[/itex] is a solution to the correspoding homogenous equation, so this implies that [itex]V_n = c_1V_{n-1} + c_2V_{n-2}[/itex]. If [itex]V_n + g(n)[/itex] is a solution to the inhomogenous equaiton, then

[tex]\begin{align*}
V_n + g(n) &= c_1(V_{n-1} + g(n-1)) + c_2(V_{n-2} + g(n-2)) + f(n) \\
&= c_1V_{n-1} + c_2V_{n-2} + c_1g(n-1) + c_2g(n-2) + f(n) \\
&= V_n + c_1g(n-1) + c_2g(n-2) + f(n)
\end{align}[/tex]

Hence, [itex]g(n) = c_1g(n-1) + c_2g(n-2) + f(n)[/itex] which statisfies the inhom. recurrence relation and so g(n) must be a solution of it. Maybe this is what you guys have been saying all along, but I'm just to dense to see it.
 

FAQ: 2. Order Linear Inhomogenous Recurrence Relations with Constant Coefficients

What is a 2nd Order Linear Inhomogenous Recurrence Relation with Constant Coefficients?

A 2nd Order Linear Inhomogenous Recurrence Relation with Constant Coefficients is a type of mathematical equation that describes a sequence of numbers, where each term is a linear combination of the previous two terms with a constant coefficient. It is "inhomogenous" because it includes a term that is not related to the previous terms, and "constant coefficients" because the coefficients of the equation do not change throughout the sequence.

What is the difference between a linear and non-linear recurrence relation?

A linear recurrence relation is one where the terms are related to the previous terms through a linear combination, meaning the terms are added or subtracted with a constant coefficient. A non-linear recurrence relation, on the other hand, involves terms that are multiplied or divided by the previous terms, making the equation non-linear.

What does it mean for a recurrence relation to be inhomogenous?

An inhomogenous recurrence relation means that the equation includes a term that is not related to the previous terms. In other words, there is an additional factor or constant in the equation that does not depend on the previous terms.

How do you solve a 2nd Order Linear Inhomogenous Recurrence Relation with Constant Coefficients?

To solve a 2nd Order Linear Inhomogenous Recurrence Relation with Constant Coefficients, you can use the characteristic equation method. This involves finding the roots of the characteristic equation, which is derived from the original recurrence relation. The roots of the characteristic equation are then used to find the general solution for the recurrence relation.

What are some real-world applications of 2nd Order Linear Inhomogenous Recurrence Relations with Constant Coefficients?

2nd Order Linear Inhomogenous Recurrence Relations with Constant Coefficients can be used to model various phenomena in different fields, such as population growth, financial markets, and physics. For example, the Fibonacci sequence, which is a type of 2nd Order Linear Inhomogenous Recurrence Relation, can be used to model the growth of a population of rabbits or the branching of a tree. In finance, these types of equations can be used to model the fluctuations of stock prices over time. In physics, they can be used to describe the behavior of oscillating systems.

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