# 	Convolve and correlate with no assumptions off end of data.
#
subroutine convin( conj, add, nx, xx, nb, bb, yy)
integer ib, iy,ny, conj, add, nx,     nb
real	xx(nx)			# input signal
real	bb(nb)			# filter      (or output crosscorrelation)
real	yy(nx-nb+1)		# filtered signal (or second input signal)
ny = nx - nb + 1		# length of filtered signal
if( ny < 1 )  call erexit('convin() filter output negative length.')
call conjnull(     conj, add,         bb, nb, yy, ny)
if( conj == 0 )
	do iy= 1, ny {
	do ib= 1, nb {
			yy( iy) = yy( iy) + bb(ib) * xx( iy-ib+nb)
			}}
else
	do ib= 1, nb {
	do iy= 1, ny {
			bb( ib) = bb( ib) + yy(iy) * xx( iy-ib+nb)
			}}
return; end