Module sciport_rs::signal

Signal Processing

The signal processing toolbox currently contains some filtering functions, a limited set of filter design tools,
and a few B-spline interpolation algorithms for 1- and 2-D data. While the B-spline algorithms could
technically be placed under the interpolation category, they are included here because they only work with
equally-spaced data and make heavy use of filter-theory and transfer-function formalism to provide a fast B-spline transform.
To understand this section, you will need to understand that a signal in sciport-rs is an array of real or complex numbers.

Filter Design

Time-discrete filters can be classified into finite response (FIR) filters and infinite response (IIR) filters.
FIR filters can provide a linear phase response, whereas IIR filters cannot.
sciport-rs provides functions for designing both types of filters.

IIR Filter

sciport-rs provides two functions to directly design IIR iirdesign and iirfilter, where the filter type (e.g., elliptic)
is passed as an argument and several more filter design functions for specific filter types, e.g., ellip.

Filter coefficients

Filter coefficients can be stored in several different formats:

• Ba
• Zpk
• Sos (currently unsupported)

References:

The documentation on this page is largely been copied from the SciPy documentation

Modules

• band_filter
• bessel
  Bessel/Thomson digital and analog filter design.
• butter
  Butterworth digital and analog filter design.
• butterord
• cheby1
  TODO! currently the bandstop option is broken, still no idea why
• cheby2
• ellip
• output_type
• tools

Enums

• Analog

Traits

• IIRFilter

Functions

• iir_filter
  Generic iir_filter