cupyx.scipy.signal.cont2discrete(system, dt, method='zoh', alpha=None)[source]#

Transform a continuous to a discrete state-space system.

  • system (a tuple describing the system or an instance of lti) –

    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)

  • dt (float) – The discretization time step.

  • method (str, optional) –

    Which method to use:

    • gbt: generalized bilinear transformation

    • bilinear: Tustin’s approximation (“gbt” with alpha=0.5)

    • euler: Euler (or forward differencing) method (“gbt” with alpha=0)

    • backward_diff: Backwards differencing (“gbt” with alpha=1.0)

    • zoh: zero-order hold (default)

    • foh: first-order hold (versionadded: 1.3.0)

    • impulse: equivalent impulse response (versionadded: 1.3.0)

  • alpha (float within [0, 1], optional) – The generalized bilinear transformation weighting parameter, which should only be specified with method=”gbt”, and is ignored otherwise


sysd – Based on the input type, the output will be of the form

  • (num, den, dt) for transfer function input

  • (zeros, poles, gain, dt) for zeros-poles-gain input

  • (A, B, C, D, dt) for state-space system input

Return type:

tuple containing the discrete system


By default, the routine uses a Zero-Order Hold (zoh) method to perform the transformation. Alternatively, a generalized bilinear transformation may be used, which includes the common Tustin’s bilinear approximation, an Euler’s method technique, or a backwards differencing technique.