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Navigation: Home
\ Education
\ Other \ Neuroph for Windows
Neuroph for Windows2.9 by Zoran Sevarac |
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Software Description:
... common neural network architectures. It contains well designed, open source Java library with small number of basic ... neural network components. It has been released as open source under the Apache 2.0 license, and it's FREE for you to use it. ...
type: Open Source
Download Neuroph for Windowscategories: neural network, neural network architectures, NN concept, neural, architecture Add to Download Basket Report virus or spyware |
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Best Vista Download periodically updates pricing and software information of Neuroph for Windows full version from the publisher,
but some information may be out-of-date. You should confirm all information. Software piracy is theft, using crack, warez passwords, patches, serial numbers, registration codes, key generator, keymaker or keygen for Neuroph for Windows license key is illegal and prevent future development of Neuroph for Windows. Download links are directly from our mirrors or publisher's website, Neuroph for Windows torrent files or shared files from rapidshare, yousendit or megaupload are not allowed! |
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| Released: | November 20, 2014 |
| Filesize: | 211.00 MB |
| Platform: | Windows XP, Windows Vista, Windows 7 |
| Install | Instal And Uninstall |
| Add Your Review or Windows Vista Compatibility Report |
Neuroph for Windows- Releases History |
| Software: | Neuroph for Windows 2.9 |
| Date Released: | Nov 20, 2014 |
| Status: | New Release |
| Software: | Neuroph for Windows 2.85 |
| Date Released: | Aug 24, 2014 |
| Status: | New Release |
| Release Notes: | Update center for NeurophStudio is available at http://neuroph.sourceforge.net/neurophstudio-uc/updates.xml You can check and get updates online automaticaly! Maven repository: http://neuroph.sourceforge.net/maven2/ SVN: http://svn.code.sf.net/p/neuroph/code/trunk |
| Software: | Neuroph for Windows 2.7 |
| Date Released: | Jan 11, 2013 |
| Status: | New Release |
| Release Notes: | 1. Performance improvements about 30% thanks to use of plain arrays instead of ArrayList collection for storing layers, neurons and connections (thanks to Borislav Markov on idea and help with this) 2. Listing of supported input functions, transfer functions, learning rues, neuron and layer classes using API - through Neuroph class 3. New class DataSet which replace old TrainingSet class (beside nameing change which now prevents confusion with Test and Validation sets, there are some implementation changes and same class is used for storing supervised and unsupervised data sets) 4. Greatly improved visual editor in Neuroph Studio with full component pallete - everything you have on framework level now you can simpy drag n' drop (thanks to Marjan Hrzic and Uros Stojkic from University of Belgrade for help with this) 5. Weights histogram in Neuroph Studio (thanks to prof Maureen Doyle, Jim Neilan and Raj Akula from Northern Kentucky University for this contribution) |
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