Sure, I would be happy to help you solve the integral equation with kernel K(st). First, let's define the integral equation with kernel K(st) as:
f(t) = g(t) + ∫K(t,s)f(s)ds
where f(t) is the unknown function, g(t) is the given function, and K(t,s) is the kernel function.
To solve this equation, we can use the method of successive approximations. We start by assuming an initial guess for f(t) and plug it into the right-hand side of the equation. This will give us a new function, which we can then use as our next guess for f(t). We repeat this process until we get a sequence of functions that converge to the solution of the integral equation.
The key to this method is choosing a good initial guess for f(t). One approach is to choose a function that satisfies the boundary conditions of the problem. Another approach is to use a simpler version of the integral equation, such as setting K(t,s) = 1, and solving it to get an initial guess.
Once we have a good initial guess, we can use numerical methods, such as the trapezoidal rule or Simpson's rule, to evaluate the integral on the right-hand side of the equation. This will give us a new function, which we can then use as our next guess for f(t). We continue this process until we reach a level of accuracy that is satisfactory.
I hope this helps you solve the integral equation with kernel K(st). If you need further assistance, please let me know.