IT++ 4.2.0 freeware

IT++ is a C++ library of mathematical, signal processing and communication classes and functions. Its main use is in simulation of communication systems and for performing research in the area of communications. The kernel of the library consists of generic vector and matrix classes, and a set of accompanying routines. Such a kernel makes IT++ similar to MATLAB or GNU Octave. ...

Author Sourceforge
Released 2011-09-15
Filesize 1.30 MB
Downloads 1045
OS Windows 2000, Windows 2003, Windows XP, Windows Vista, Windows 7, Linux, Mac OS X
Installation Instal And Uninstall
Keywords signal processing, communication classes, communication function, process, signal, communication
Users' rating
(16 rating)
IT++Components & LibrariesWindows 2000, Windows 2003, Windows XP, Windows Vista, Windows 7, Linux, Mac OS X
IT++ - network analysis Freeware Download Notice

IT++ Free Download - we do not host any IT++ torrent files or links of IT++ on rapidshare.com, depositfiles.com, megaupload.com etc. All IT++ download links are direct IT++ download from publisher site or their selected mirrors.

IT++ freeware - The Latest User Reviews
IT++ freeware - The Latest Versions History
4.2.0 Sep 15, 2011 New Release * Added SISO class implementing several algorithms used in turbo decoders/
receivers
* Added EXIT class for EXIT chart computation of turbo receivers
* Added STC class for the generation of Space Time block codes used in MIMO
systems with turbo receivers
* Added support for testing IT++ library in Visual Studio 2008. Current approach
relies on fc (file compare) utility which seems to be available only in Visual
Studio 2008.
* Added rank() function, which calculates the rank of a matrix by counting
the number of non-zero singular values. SVD function from LAPACK is thus
required by this function.
* Added implementation of Gamma(alpha, beta) random number generator. The
implementation of the Gamma_RNG::sample() function was taken from the R
statistical language.
* Added qr() overloaded function that does not compute Q. For some tasks
(triangularization) the Q matrix is not really needed.

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