The filters available in the LabVIEW Digital Filter Design Toolkit can have the following attributes: digital, linear, time-invariant, or causal.

The filters that you design using the LabVIEW Digital Filter Design Toolkit have the following attributes:

  • Digital—The expected filter input signal is a series of discrete digital values. The set of discrete digital coefficients determines the filter frequency response. Digital filters have many advantages over analog filters. For example, the frequency response of digital filters generally does not depend on the parametric variation of electronic components, power supply noise, or power supply droop.
  • Linear—The output signal of the digital filter is a linear function of the input signal. You cannot use the digital filter to equalize nonlinear distortion caused by passing a signal through a nonlinear peak-clipping or truncating channel.
  • Time-invariant—The frequency response of the digital filter is fixed versus time. Alternatively, adaptive filters, which the Digital Filter Design Toolkit does not support, can adapt their frequency responses versus time in response to time-variant target responses.
  • Causal—The output signal of a digital filter cannot change in response to a change in an input signal until the input signal changes. The Digital Filter Design Toolkit specifically creates digital filters that you treat as causal in applications, but you can use them in some noncausal applications. For example, a common Digital Signal Processing (DSP) technique for linearizing the phase of a filter with a nonlinear phase is to pass the input signal through the filter, time-reverse the input signal, and then pass the signal through the filter again. In this case, the filter is noncausal.