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University of Jyväskylä
Department of Mathematical Information Technology
NDA - Neural Data Analysis environment
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Neural Data Analysis (NDA)
A generally applicable software kernel for data analysis and data mining tasks.
- The NDA provides a large set of methods for data manipulation, data reduction, data visualization and decision making.
- The most important algorithms in the software are the Tree Structured Self-Organizing Map, the Multilayer Perceptron network with the mostly used variants of the backpropagation algorithm, multivariate statistics, and a lot of data processing methods.
- Please navigate the software through the figure:
- The NDA supports best the interactive SOM analysis. See an example.
The Software Architecture
The NDA is a portable software kernel.
- It is independent of used operating systems and graphical environments:
It is easy to be ported for different operating systems (Windows, Unix).
It can be used with different development environments (Java, Motif, Excel, Visual Basic,...).
- The kernel can be easily tailored for different applications.
See more about the architecture of the NDA.
Applications and examples
NDA is used either as a data analysis tool or as a software kernel in applications. Our collaborators have built their own software products based on the NDA kernel. Some examples are
- Process monitoring and control, analysis of process data (Visipoint Ltd, Pechiney ElectroMetallurgy)
- Quality control of the print paper (Hormell Ltd)
- Detection of similar text documents (Sonera Ltd)
- Analysis of qualitative data (CATO project)
- Decision support in logistics planning (UPM-Kymmene Logistics Ltd)
- Air quality control and prediction (Laboratory of Environmental Chemistry)
- Analysis and visualization of gene expressions (Visipoint Ltd)
Documents
User's command reference: User's Guide.
(Latest old version of User's Guide.)
(Old version of User's Guide.)
(Even older version of User's Guide.)
(Ancient version of User's Guide.)
Distribution
Index for distributed files (password needed)
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This page was last modified on May 31st, 2000 by Erkki Häkkinen