# neural network
tabular wgt % 25 -12 12 1/25
f(u)=1/(1+exp(-beta*u))
special k=conv(even,51,12,wgt,u0)
u[0..50]'=-u[j]+f(a*k([j])-c*delay(u[j],tau)-thr)
par c=8,a=9,beta=10,thr=1,tau=4
init u0=1,u1=1
@ total=10,delay=10,xhi=10,ylo=0,yhi=1,yp=u20
done