Package to solve linear inverse problems
LinvPy is a Python package designed for solving linear inverse problems of the form y=Ax+n, where y is a vector of measured values, A a known matrix, x an unknown input vector and n is noise. The goal is to find x, or at least the best possible estimation; if the matrix A is invertible, the solution is easy to find by multiplying by the inverse, if not, we need to use regression techniques such as least squares method to find x. The first motivation for this project is that Marta Martinez-Camara, PhD student in Communications Systems at EPFL (Switzerland) desgined some new algorithms for solving linear inverse problems, and this package is a Python implementation of these algorithms, which may not be available anywhere else than here. LinvPy also contains several other known and available techniques such as least squares regression, regularization functions, loss functions or M-estimators which you can also find in the famous Numpy or Scipy packages.
To install from pip, simply run : $ pip install linvpy
PyPi link : https://pypi.python.org/pypi/linvpy
ReadTheDocs link : http://linvpy.readthedocs.org/en/latest/
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