Release v4.0.0

This release redesigns the core of the RCNet library. It brings an unified hidden neuron and introduces:

• new ability of hidden neurons having analog activations to produce spikes similarly to spiking activations. This also brings a new ability to classify very accurately and quickly using a classical analog ESN reservoir (results look really great)
• dynamic synapse enabling correct communication between hidden neurons having different activations
• unified set of available predictors
• automatic blocking of predictors that give almost constant values. It prevents readout layer learning failure
• simplified and improved xml setup
• Elastic net regression

This fundamental modification also shows that by combining analog and spiking activations, better results can be achieved than each separately. However, this assumption has yet to be verified and will be the main topic of further research.