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Submitted: 05/12/2008
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COmpartment Model Kinetic Analysis Tool
Category:
Medical Engineering and Research
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COMKAT, which stands for 'COmpartment Model Kinetic Analysis Tool', is MATLAB software for compartmental modeling oriented to nuclear medicine applications (PET & SPECT). It supports models of a wide range complexity including multiple injection, receptor model with saturation. It supports many image formats, including DICOM images. Using either the command line interface or GUI, models are easily specified, solved or used to fit experimental data. Sensitivity equations are supported. No mathematical derivations are required on the part of the user.
http://comkat.case.edu/comkat/comkat_wiki/index.php?title=Home
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Submitted: 05/09/2008
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DACE Toolbox
Category:
Mathematics>Fitting and Interpolation
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From DTU - IMM:
DACE, Design and Analysis of Computer Experiments, is a Matlab toolbox for working with kriging approximations to computer models.
Typical use of this software is to construct a kriging approximation model based on data from a computer experiment, and to use this approximation model as a surrogate for the computer model.
The software also addresses the design of experiment problem, that is choosing the inputs at which to evaluate the computer model for constructing the kriging approximation.
http://www2.imm.dtu.dk/~hbn/dace/
Submitted by Thierry Dalon
Updated May 12, 2008
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Submitted: 05/09/2008
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Submitted: 05/09/2008
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Genetic Algorithm Optimization Toolbox (GAOT)
Category:
Optimization>Genetic algorithms
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GAOT implements simulated evolution in the Matlab environment using both binary and real representations. Ordered base representation has also been added to the toolbox. This implementation is very flexible in the genetic operators, selection functions, termination functions as well as the evaluation functions that can be used. The implementation is described in a technical paper. The paper can be referenced as follows:
"A Genetic Algorithm for Function Optimization: A Matlab Implementation" by Chris Houck, Jeff Joines, and Mike Kay, NCSU-IE TR 95-09, 1995.
http://www.ise.ncsu.edu/mirage/GAToolBox/gaot/
Submitted by Thierry Dalon
Updated May 12, 2008
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Submitted: 05/09/2008
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Submitted: 05/09/2008
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NNSYSID Toolbox
Category:
Neural Networks
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The NNSYSID toolbox is a set of MATLAB tools for neural network based identification of nonlinear dynamic systems. The toolbox contains a number of m and MEX-files for training and evaluation of multilayer perceptron type neural networks within the MATLAB environment. There are functions for training of ordinary feedforward networks as well as for identification of nonlinear dynamic systems and for time-series analysis. Version 2 requires MATLAB 5.3 or higher. For MATLAB 4.2-MATLAB 5.2 it is possible to use the old Version 1.1. In this case the Signal Processing Toolbox must be available. The toolbox is completely independent of the Neural Network Toolbox and the System Identification Toolbox.
The toolbox contains:
Fast, robust, and easy-to-use training algorithms.
A number of different model structures for modelling of dynamic systems.
Validation of trained network models.
Estimation of the models's generalization ability.
Demonstration programs.
http://www.iau.dtu.dk/research/control/nnsysid.html
Submitted by Thierry Dalon
Updated May 12, 2008
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Submitted: 05/02/2008
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Submitted: 04/30/2008
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Submitted: 04/24/2008
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Text to Matrix Generator (TMG)
Category:
Utilities
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Text to Matrix Generator (TMG) is a MATLAB� toolbox that can be used for various tasks in text mining (TM). Most of TMG (version 4.0) is written in MATLAB, though a large segment of the indexing phase of the current version of TMG is written in Perl. Previous versions that were strictly MATLAB are also available. If MySQL and the MATLAB Database Toolbox are available, TMG exploits their functionality for additional flexibility.
TMG is especially suited for TM applications where data is high-dimensional but extremely sparse as it uses the sparse matrix infrastructure of MATLAB.
http://scgroup6.ceid.upatras.gr:8000/wiki/index.php/Main_Page
Submitted by Efstratios Gallopoulos
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Submitted: 04/14/2008
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Submitted: 04/14/2008
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Submitted: 04/14/2008
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Submitted: 04/14/2008
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