Solving an Integral Equation with Separable Kernels

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In summary, an integral equation with separable kernels is a mathematical equation that involves an unknown function under an integral sign with a separable kernel function. It is commonly used in physics, engineering, and other fields to model real-world problems. To solve such equations, the separable kernel function needs to be identified and split into two functions, followed by using the method of separation of variables to rewrite the equation and finding the unknown function. The advantages of using separable kernels include simplification of the equation, analytical solutions, and generalization to higher dimensions. However, there are limitations to this method, such as not all equations being solvable and the method of separation of variables not always working for complex equations. Real-world applications of solving integral equations
  • #1
Dustinsfl
2,281
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Checking to see if my solution is correct.

Solve the integral equation
\[
f(x) = 1 + \lambda\int_0^1\big(xy + x^3y^2\big)f(y)dy
\]
using the method of separable kernels

We need to rewrite \(f(x)\).
\[
f(x_i) = 1 + \sum_{i = 1}^2x^{2i - 1}A_i
\]
where \(A_i = \lambda\int_0^1y^if(y)dy\). Let \(f(y_i) = 1 + \sum\limits_{i = 1}^2y^{2i - 1}A_i\). Then
\begin{align*}
A_i &= \lambda\int_0^1y^i\Bigg(1 + \sum_{j = 1}^2y^{2j - 1}A_j\Bigg)dy\\
&= \lambda\int_0^1y^idy +
\lambda\sum_{j = 1}^2A_j\int_0^1y^{2j - 1}y^idy\\
\sum_{j = 1}^2\Bigg(\delta_{ij} - \lambda\int_0^1y^{2j - 1}y^idy\Bigg)A_j
&= \lambda\int_0^1y^idy\\
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix}
&= \lambda
\begin{pmatrix}
\frac{1}{2}\\
\frac{1}{3}
\end{pmatrix}\\
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} &=
\begin{pmatrix}
-\frac{3\lambda(\lambda - 30)}{180 + \lambda(\lambda - 90)}\\[.3cm]
\frac{5\lambda(\lambda + 24)}{360 + 2\lambda(\lambda - 90)}
\end{pmatrix}
\end{align*}
Therefore, \(f(x_i)\) is
\[
\begin{pmatrix}
f(x_1)\\
f(x_2)
\end{pmatrix} =
\begin{pmatrix}
-x\frac{3\lambda(\lambda - 30)}{180 + \lambda(\lambda - 90)}\\[.3cm]
x^3\frac{5\lambda(\lambda + 24)}{360 + 2\lambda(\lambda - 90)}
\end{pmatrix}.
\]
Additionally, if the determinant of
\[
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
= 0,
\]
then we only have a solution if \(v_i(y) = \int_0^1y^idy = 0\).
\[
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} =
\begin{pmatrix}
A_1\Big(1 - \frac{\lambda}{3}\Big) - \frac{\lambda A_2}{5}\\
A_2\Big(1 - \frac{\lambda}{6}\Big) - \frac{\lambda A_1}{4}
\end{pmatrix} =
\mathbf{0}
\]
Therefore, \(A_i\) is
\[
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} =
\begin{pmatrix}
1\\
0
\end{pmatrix}
\]
and \(f(x_i)\) is
\[
\begin{pmatrix}
f(x_1)\\
f(x_2)
\end{pmatrix} =
\begin{pmatrix}
1 + x\\
1
\end{pmatrix}.
\]
 
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  • #2
dwsmith said:
Checking to see if my solution is correct.

Solve the integral equation
\[
f(x) = 1 + \lambda\int_0^1\big(xy + x^3y^2\big)f(y)dy
\]
using the method of separable kernels

We need to rewrite \(f(x)\).
\[
f(x_i) = 1 + \sum_{i = 1}^2x^{2i - 1}A_i
\]
where \(A_i = \lambda\int_0^1y^if(y)dy\). Let \(f(y_i) = 1 + \sum\limits_{i = 1}^2y^{2i - 1}A_i\). Then
\begin{align*}
A_i &= \lambda\int_0^1y^i\Bigg(1 + \sum_{j = 1}^2y^{2j - 1}A_j\Bigg)dy\\
&= \lambda\int_0^1y^idy +
\lambda\sum_{j = 1}^2A_j\int_0^1y^{2j - 1}y^idy\\
\sum_{j = 1}^2\Bigg(\delta_{ij} - \lambda\int_0^1y^{2j - 1}y^idy\Bigg)A_j
&= \lambda\int_0^1y^idy\\
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix}
&= \lambda
\begin{pmatrix}
\frac{1}{2}\\
\frac{1}{3}
\end{pmatrix}\\
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} &=
\begin{pmatrix}
-\frac{3\lambda(\lambda - 30)}{180 + \lambda(\lambda - 90)}\\[.3cm]
\frac{5\lambda(\lambda + 24)}{360 + 2\lambda(\lambda - 90)}
\end{pmatrix}
\end{align*}
Therefore, \(f(x_i)\) is
\[
\begin{pmatrix}
f(x_1)\\
f(x_2)
\end{pmatrix} =
\begin{pmatrix}
-x\frac{3\lambda(\lambda - 30)}{180 + \lambda(\lambda - 90)}\\[.3cm]
x^3\frac{5\lambda(\lambda + 24)}{360 + 2\lambda(\lambda - 90)}
\end{pmatrix}.
\]
Additionally, if the determinant of
\[
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
= 0,
\]
then we only have a solution if \(v_i(y) = \int_0^1y^idy = 0\).
\[
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} =
\begin{pmatrix}
A_1\Big(1 - \frac{\lambda}{3}\Big) - \frac{\lambda A_2}{5}\\
A_2\Big(1 - \frac{\lambda}{6}\Big) - \frac{\lambda A_1}{4}
\end{pmatrix} =
\mathbf{0}
\]
Therefore, \(A_i\) is
\[
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} =
\begin{pmatrix}
1\\
0
\end{pmatrix}
\]
and \(f(x_i)\) is
\[
\begin{pmatrix}
f(x_1)\\
f(x_2)
\end{pmatrix} =
\begin{pmatrix}
1 + x\\
1
\end{pmatrix}.
\]

olve the integral equation
\[
f(x) = 1 + \lambda\int_0^1\big(xy + x^3y^2\big)f(y)dy
\]
using the method of separable kernels

We need to rewrite \(f(x)\).
\[
f(x) = 1 + \sum_{i = 1}^2x^{2i - 1}A_i
\]
where \(A_i = \lambda\int_0^1y^if(y)dy\). Let \(f(y_i) = 1 + \sum\limits_{i = 1}^2y^{2i - 1}A_i\). Then
\begin{align*}
A_i &= \lambda\int_0^1y^i\Bigg(1 + \sum_{j = 1}^2y^{2j - 1}A_j\Bigg)dy\\
&= \lambda\int_0^1y^idy +
\lambda\sum_{j = 1}^2A_j\int_0^1y^{2j - 1}y^idy\\
\sum_{j = 1}^2\Bigg(\delta_{ij} - \lambda\int_0^1y^{2j - 1}y^idy\Bigg)A_j
&= \lambda\int_0^1y^idy\\
\begin{pmatrix}
1 - \frac{\lambda}{3} & -\frac{\lambda}{5}\\
-\frac{\lambda}{4} & 1 - \frac{\lambda}{6}
\end{pmatrix}
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix}
&= \lambda
\begin{pmatrix}
\frac{1}{2}\\
\frac{1}{3}
\end{pmatrix}\\
\begin{pmatrix}
A_1\\
A_2
\end{pmatrix} &=
\begin{pmatrix}
-\frac{3\lambda(\lambda - 30)}{180 + \lambda(\lambda - 90)}\\[.3cm]
\frac{5\lambda(\lambda + 24)}{360 + 2\lambda(\lambda - 90)}
\end{pmatrix}
\end{align*}
Then the solution is
\[
f(x) = 1 -x\frac{3\lambda(\lambda - 30)}{180 + \lambda(\lambda - 90)} + x^3 \frac{5\lambda(\lambda + 24)}{360 + 2\lambda(\lambda - 90)}.
\]
 

FAQ: Solving an Integral Equation with Separable Kernels

What is an integral equation with separable kernels?

An integral equation with separable kernels is a type of mathematical equation that involves an unknown function appearing under an integral sign with a separable kernel function. This means that the kernel function can be written as a product of two functions, one depending only on the variable of integration and the other on the unknown function. These types of equations are commonly used in physics, engineering, and other fields to model real-world problems.

How do you solve an integral equation with separable kernels?

To solve an integral equation with separable kernels, you need to follow some specific steps. First, you need to identify the separable kernel function and split it into two functions. Then, you can use the method of separation of variables to rewrite the integral equation as two separate equations. Next, you can solve each of the equations separately, and finally, combine the solutions to find the unknown function.

What are the advantages of using separable kernels in integral equations?

Using separable kernels in integral equations has several advantages. One of the main advantages is that it simplifies the equation, making it easier to solve. Additionally, separable kernels often lead to analytical solutions, which can provide insight into the behavior of the unknown function. They also allow for easy generalization to higher dimensions, making them useful for solving multi-dimensional problems.

Are there any limitations to using separable kernels in integral equations?

Yes, there are some limitations to using separable kernels in integral equations. One limitation is that not all integral equations can be written in terms of separable kernels. Additionally, the method of separation of variables may not always work, especially for more complex equations. In these cases, other numerical or analytical methods may need to be used to solve the equation.

What are some real-world applications of solving integral equations with separable kernels?

Solving integral equations with separable kernels has many real-world applications. Some examples include modeling heat transfer in physics, solving differential equations in engineering, and analyzing population dynamics in biology. They are also commonly used in image processing, signal processing, and data analysis. In general, any problem that can be described using an integral equation with a separable kernel can benefit from this method of solving.

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