of array_like
    describing the system.
    The following gives the number of elements in the tuple and
    the interpretation:

        * 1 (instance of `lti`)
        * 2 (num, den)
        * 3 (zeros, poles, gain)
        * 4 (A, B, C, D)

X0 : array_like, optional
    Initial state-vector.  Defaults to zero.
T : array_like, optional
    Time points.  Computed if not given.
N : int, optional
    The number of time points to compute (if `T` is not given).

Returns
-------
T : ndarray
    A 1-D array of time points.
yout : ndarray
    A 1-D array containing the impulse response of the system (except for
    singularities at zero).

Notes
-----
If (num, den) is passed in for ``system``, coefficients for both the
numerator and denominator should be specified in descending exponent
order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).

Examples
--------
Compute the impulse response of a second order system with a repeated
root: ``x''(t) + 2*x'(t) + x(t) = u(t)``

>>> from scipy import signal
>>> system = ([1.0], [1.0, 2.0, 1.0])
>>> t, y = signal.impulse(system)
>>> import matplotlib.pyplot as plt
>>> plt.plot(t, y)

z6impulse can only be used with continuous-time systems.r˜