PyDSM is a Python Delta Sigma Modulator toolbox. It contains tools for experimenting with ΔΣ modulators. It focuses mostly on experimentation with different techniques for the design of the modulator Noise Transfer Function (NTF) and simulation of a generic digital modulator.
|Tags||Delta Sigma Modulation Optimization|
|Licenses||New BSD License|
|Operating Systems||Linux Windows (MinGW)|
|Implementation||Python Cython Scipy|
Release Notes: This version fixes a regression introduced in 0.7.3; upgrading is recommended. It includes the following changes: a new NTF design method based on a noise weighting function; standard audio weighting functions and ISO 226 equal loudness contours; new NTF design methods for psychoacoustically optimal modulators for audio signals; a regression fix in ds_optzeros (the regression was preventing some example code from running); new examples from a recently published TCAS-II paper; and a 'ba' specifier for filters in numerator/denominator form. The evalTF function is more robust against complex overflow, and there are some bugfixes.
Release Notes: This release makes the codebase compatible with scipy 0.12.0, makes the delsig module contain its reference delsig version, and makes minor fixes to the documentation.
Release Notes: This version includes a port of the synthesizeChebyshevNTF NTF design strategy and some bugfixes. It avoids deprecated direct access to numpy array data to make it compatible with future numpy releases.
Release Notes: By dropping an external dependecy, deployment in Windows is now much easier, and Windows installers are now available.
Release Notes: This release splits the download into a main code download and a documentation download, and provides sample code to replicate the results in some scientific papers.