Neuroph is lightweight Java neural network framework which can be used to simulate common neural network architectures, It has fast learning curve with small number of basic classes which correspond to basic NN concepts.

If you are beginner with neural networks, you just want to try how they work without going into complicated theory and implementation, or you need them for your research project the Neuroph is for you.

Neuroph supports the following NN architectures:

Adaline
Perceptron
Multi Layer Perceptron
Hopfield
Kohonen
NFR (Neuro Fuzzy Reasoner)

Neuroph is a small, well documented, easy to use, but very flexible neural network framework.

What's New in This Release: [ read full changelog ]

· Perceptron and MultiLayerPerceptron now have Linear transfer functions in input layer (looks like this improved learning, and thats right to do)
· Changed the way ThresholdNeuron calculates output - it used to compare total input with thershold, now it does substraction totalInput-thresh.
· Since it has Step transfer function on output it makes no difference on final result, but it has better model for visualisation.
· Training monitor is now displayed as internal frame so it does not hide behind the main frame.
· New icons for toolbar buttons
· Created start.bat for easyneurons
· Default initial setting of max error 0.01 for all supervised learning rules (many users forget to set this setting when training from code)
· Added load(InputStream inputStream) method to NeuralNetwork class to enable the use of getResourceAsStream to load neural network from jar.
· Added BiasNeuron class, which provides bias feature for MLPs and other networksBias neuron allways has high output level, and dont has inputs...