# computing r(t)=int_0^t D(t') s(t-t') dt'
# some numerical setups
@ dt=10,total=10000
@ autoeval=0
# define the white noise as a table pf values so that you can use them
# over again
table s % 1001 0 10000 normal(0,1)*sqrt(10/dt)
# parameters 
par dt=10,r0=10,tau=.02
# here is the kernel
d(t)=-cos(2*pi*(t-20)/140)*exp(-t/60)
#
y=s(t)
# here is the convolution
r(t)=int{d(t)#y}+r0
# just to see the stimulus as well
aux stim=s(t)
done