havFmNet:J - Java classes for Self-Organizing Feature Map Neural Networks (SOM) and Kohonen Maps
hav.Software
hav.Software
Neural Net class libs - C++ and Java havFmNet:JTM
Java classes for implementing 1D to nD Self-Organizing Feature Maps


havFmNet:JTM is focused on implementation of the underlying NN functions/activities rather than the higher-level simulator/UI. It is designed to be fully embedable; however, it can, as easily, be used to implement stand-alone training or consultation applications. The typical application can take advantage of the layer oriented API to define either simple nets or very complicated and large nets consisting of one or more sub-nets.

You might also take a look at the Online Documentation for more detailed information.

havFmNet
Features
havFmNet 1D to nD maps with fully "hyper" neighborhood function and parameters.
Notice: The JavaScript Neural Nets web-demo contains a conultation application using a 3-D Map trained using havFmNet:J.
havFmNet Neighborhood controlable by...
  • function width,
  • coefficient cutoff and
  • block size (i.e. hypercube size).
havFmNet Nodes addressable by 1D or nD index values.
havFmNet Error query per map or per node
havFmNet Selectable conscience, learning rate, batch size, noise, etc.
havFmNet On-Center-Off-Surround training with a sombrero form of Kohonen's neighborhood function.

on Center-off Surround
Click for larger view




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