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perl-Math-KalmanFilter
perl-Math-KalmanFilter.spec
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File perl-Math-KalmanFilter.spec of Package perl-Math-KalmanFilter
# # spec file for package perl-Math-KalmanFilter # # Copyright (c) 2016 SUSE LINUX GmbH, Nuernberg, Germany. # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed # upon. The license for this file, and modifications and additions to the # file, is the same license as for the pristine package itself (unless the # license for the pristine package is not an Open Source License, in which # case the license is the MIT License). An "Open Source License" is a # license that conforms to the Open Source Definition (Version 1.9) # published by the Open Source Initiative. # Please submit bugfixes or comments via http://bugs.opensuse.org/ # Name: perl-Math-KalmanFilter Version: 0.07 Release: 0 %define cpan_name Math-KalmanFilter Summary: Kalman Filter(also known as Linear Quadratic Estimation) implementation [cut] License: Artistic-1.0 or GPL-1.0+ Group: Development/Libraries/Perl Url: http://search.cpan.org/dist/Math-KalmanFilter/ Source0: http://www.cpan.org/authors/id/S/SH/SHANTANU/%{cpan_name}-%{version}.tar.gz BuildArch: noarch BuildRoot: %{_tmppath}/%{name}-%{version}-build BuildRequires: perl BuildRequires: perl-macros BuildRequires: perl(Moose) Requires: perl(Moose) %{perl_requires} %description The Kalman filter, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone. Algorithm is recursive, which means it takes the output of its previous calculations as a factor in calculating the next step which improves its accuracy over time. The key to Kalman filters are two sensors with different kind of accuracy issues in each. Sensor A or the state sensor might give in-accurate value for a measurement on the whole but it doesn't drift. Sensor B or delta sensor gives gives much more accurate rate of change in value(or delta) but it drifts over time due to its small inaccuracies as it only measures rate of change in value and not the actual value. Kalman filter uses this knowledge to fuse results from both sensors to give a state value which is more accurate than state value received from any of these filters alone. An example of application for this is calculating orientation of objects using Gyroscopes and Accelerometers. While Accelerometer is usually used to measure gravity it can be used to measure the inclination of a body with respect to the surface of earth along the x and y axis(not z axis as Z axis is usually facing the opposite direction as the force of gravity) by measuring the direction in which the force of gravity is applied. Gyroscope measures the rate of rotation about one or all the axis of a body. while it gives fairly accurate estimation of the angular velocity, if we use it to calculate the current inclination based on the starting inclination and the angular velocity, there is a lot of drift, which means the gyroscope error will accumulate over time as we calculate newer angles based on previous angle and angular velocity and the error in angular velocity piles on. A real life example of how Kalman filter works is while driving on a highway in a car. If you take the time passed since when your started driving and your estimated average speed every hour and use it to calculate the distance you have traveled your calculation will become more inaccurate as you drive on. This is drift in value. However if you watch each milestone and calculate your current position using milestone data and your speed since the last milestone your result will be much more accurate. That is approximately close to how Kalman filter works. %prep %setup -q -n %{cpan_name}-%{version} %build %{__perl} Makefile.PL INSTALLDIRS=vendor %{__make} %{?_smp_mflags} %check %{__make} test %install %perl_make_install %perl_process_packlist %perl_gen_filelist %files -f %{name}.files %defattr(-,root,root,755) %doc Changes LICENSE README %changelog
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