Introduction

PyDSM is a Python toolbox for Delta Sigma Modulators. It provides tools for experimenting with ΔΣ modulators. At present, the library is still relatively small and mainly focused on exploring different techniques for designing the Noise Transfer Function (NTF). In addition, the code includes functionality to simulate a generic modulator.

PyDSM is actively developed and will be extended with new features in the near future.

Highlights of the current version include:

• Several routines ported from the well-known DELSIG toolbox for Matlab by R. Schreier.

• The method proposed by Dunn and Sandler (1997) [Dun97] for designing psychoacoustically optimal modulators for audio signals.

• The NTF design algorithms presented in [Cal13a] and [Cal13b]. The latter introduces an optimal strategy for designing psychoacoustically optimal modulators for audio signals, configurable for different noise weightings (e.g. A-Weighting, F-Weighting, user-supplied weightings, etc.). If you find this code useful, please consider citing these two papers in your work.

• The NTF design algorithm proposed in [Nag12].

• The NTF design algorithm presented in [Cal15].

PyDSM is free software and is licensed as described in the License section of this manual.

PyDSM is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranties of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Further details are provided along with the licensing information.