mxlib
c++ tools for analyzing astronomical data and other tasks by Jared R. Males. [git repo]
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sigproc.hpp
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1/** \file sigproc.hpp
2 * \author Jared R. Males
3 * \brief Library include for the sigproc module
4 * \ingroup signal_processing_files
5 *
6 */
7
8//***********************************************************************//
9// Copyright 2023 Jared R. Males (jaredmales@gmail.com)
10//
11// This file is part of mxlib.
12//
13// mxlib is free software: you can redistribute it and/or modify
14// it under the terms of the GNU General Public License as published by
15// the Free Software Foundation, either version 3 of the License, or
16// (at your option) any later version.
17//
18// mxlib is distributed in the hope that it will be useful,
19// but WITHOUT ANY WARRANTY; without even the implied warranty of
20// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
21// GNU General Public License for more details.
22//
23// You should have received a copy of the GNU General Public License
24// along with mxlib. If not, see <http://www.gnu.org/licenses/>.
25//***********************************************************************//
26
27#ifndef sigproc_hpp
28#define sigproc_hpp
29
30#include "autocorrelation.hpp"
32#include "basisUtils2D.hpp"
33#include "circularBuffer.hpp"
34#include "fourierModes.hpp"
35#include "gramSchmidt.hpp"
36#include "levinsonRecursion.hpp"
37#include "linearPredictor.hpp"
38#include "psdFilter.hpp"
39#include "psdUtils.hpp"
40#include "psdVarMean.hpp"
41#include "signalWindows.hpp"
42#include "zernike.hpp"
43
44#endif // sigproc_hpp
Tools for working with autocorrelations.
A class to manage calculation of periodograms from time series data.
Utilities for a working with a 2D basis set.
A circular buffer class.
Functions for generating 2D Fourier modes.
Procedures to orthogonalize vector basis sets.
Working with linear prediction.
Declares and defines a class for filtering with PSDs.
Tools for working with PSDs.
Tools for calculating the variance of the mean of a PSD.
Procedures to calculate window functions for signal processing.
Working with the Zernike polynomials.