  This paper considers a numeric algorithm to solve the equation \begin{align*}
y(t)=f(t)+\int^t_0 g(t-\tau)y(\tau)\,d\tau \end{align*} with a kernel $g$ and
input $f$ for $y$. In some applications we have a smooth integrable kernel but
the input $f$ could be a generalised function, which could involve the Dirac
distribution. We call the case when $f=\delta$, the Dirac distribution centred
at 0, the fundamental solution $E$, and show that $E=\delta+h$ where $h$ is
integrable and solve \begin{align*} h(t)=g(t)+\int^t_0 g(t-\tau)h(\tau)\,d\tau
\end{align*} The solution of the general case is then \begin{align*}
y(t)=f(t)+(h*f)(t) \end{align*} which involves the convolution of $h$ and $f$.
We can approximate $g$ to desired accuracy with piecewise constant kernel for
which the solution $h$ is known explicitly. We supply an algorithm for the
solution of the integral equation with specified accuracy.
