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emgr
Empirical gramians can be computed for linear and nonlinear control systems for purposes of model order reduction or system identification. Model reduction using empirical gramians can be applied to the state space, to the parameter space or to both through combined reduction. The emgr framework is a compact open source toolbox for (empirical) gramian-based model reduction and compatible with OCTAVE and MATLAB.
More informationGAP
GAP is a system for computational discrete algebra, with particular emphasis on Computational Group Theory. GAP provides a programming language, a library of thousands of functions implementing algebraic algorithms written in the GAP language as well as large data libraries of algebraic objects. GAP is used in research and teaching for studying groups and their representations, rings, vector spaces, algebras, combinatorial structures, and more. GAP is developed by international cooperation. The system, including source, is distributed freely under the terms of the GNU General Public License. You can study and easily modify or extend GAP for your special use. The current version is GAP 4, the older version GAP 3 is still available.
More informationGlobal Optimization Toolbox For Maple
Optimization is the science of finding solutions that satisfy complicated constraints and objectives. In engineering, constraints may arise from technical issues. In business, constraints are related to many factors, including cost, time, and staff. The objective of global optimization is to find [numerically] the absolute best solution of highly nonlinear optimization models that may have a number of locally optimal solutions. Global optimization problems can be extremely difficult. Frequently engineers and researchers are forced to settle for solutions that are “good enough” at the expense of extra time, money, and resources, because the best solution has not been found. Using the Global Optimization Toolbox, you can formulate your optimization model easily inside the powerful Maple numeric and symbolic system, and then use world-class Maple numeric solvers to return the best answer, fast! Illustrative references: 1. Pintér, J. D. Global Optimization in Action. Springer Science, 1996, 512 p., ISBN: 978-0-7923-3757-7 Winner of the 2000 INFORMS Computing Society Prize. 2. Pintér, J. D., Linder, D. and Chin, P. Global Optimization Toolbox for Maple: An introduction with illustrative applications. Optimization Methods and Software 21 (2006) (4) 565-582.
More informationHiFlow³
HiFlow³ is a multi-purpose finite element software providing powerful tools for efficient and accurate solution of a wide range of problems modeled by partial differential equations. Based on object-oriented concepts and the full capabilities of C++ the HiFlow³ project follows a modular and generic approach for building efficient parallel numerical solvers. It provides highly capable modules dealing with the mesh setup, finite element spaces, degrees of freedom, linear algebra routines, numerical solvers, and output data for visualization. Parallelism – as the basis for high performance simulations on modern computing systems – is introduced on two levels: coarse-grained parallelism by means of distributed grids and distributed data structures, and fine-grained parallelism by means of platform-optimized linear algebra back-ends.
More informationIBM SPSS Statistics
With IBM SPSS Statistics, you can get a quick look at your data, formulate hypotheses for additional testing, and then carry out a number of procedures to help clarify relationships between variables, create clusters, identify trends and make predictions.
More informationMaple
Maple is an environment for scientific and engineering problem-solving, mathematical exploration, data visualization and technical authoring.
More informationMatlab
MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and Fortran.
More informationPolyBoRi
The core of PolyBoRi is a C++ library, which provides high-level data types for Boolean polynomials and monomials, exponent vectors, as well as for the underlying polynomial rings and subsets of the powerset of the Boolean variables. As a unique approach, binary decision diagrams are used as internal storage type for polynomial structures. On top of this C++-library we provide a Python interface. This allows parsing of complex polynomial systems, as well as sophisticated and extendable strategies for Gröbner base computation. PolyBoRi features a powerful reference implementation for Gröbner basis computation.
More informationR
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
More informationrbMIT
The rbMIT © MIT software package implements in Matlab® all the general reduced basis algorithms. The rbMIT © MIT software package is intended to serve both (as Matlab® source) "Developers" — numerical analysts and computational tool-builders — who wish to further develop the methodology, and (as Matlab® "executables") "Users" — computational engineers and educators — who wish to rapidly apply the methodology to new applications. The rbMIT software package was awarded with the Springer Computational Science and Engineering Prize in 2009.
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