Redesign (final phase)

Readme.md

@@ -109,7 +109,7 @@ See the [wiki pages.](https://en.wikipedia.org/wiki/Biological_neuron_model)
 |HiddenNeuron|Supports both analog and spiking activation functions and can produce analog signal and/or spikes (neuron is able to fire spikes even when stateless analog activation is used). Supports Retainment property of analog activation (leaky integrator). Supports set of different predictors.|
 |Reservoir|Provides recurrent network supporting analog and spiking neurons working directly together. Main features: SpectralRadius (for weights of analog, spiking or both neurons), Multiple 3D pools of neurons, Pool to pool connections. It can work as the Echo State Network reservoir, Liquid State Machine reservoir or Mixed reservoir|
 |NeuralPreprocessor|Provides data preprocessing to predictors. Supports multiple internal reservoirs. Supports virtual input data associated with predefined signal generators. Supports two input feeding regimes: Continuous and Patterned|
-|ReadoutUnit|Readout unit does the Forecast or Classification. Contains trained output unit and related important error statistics. Trained unit can be the Feed Forward Network or the Parallel Perceptron Network|
-|ReadoutLayer|Class implements common readout layer concept for the reservoir computing methods. Supports x-fold cross validation method and clustering of the trained readout units.|
+|ReadoutUnit|Readout unit does the Forecast or Classification. Contains cluster of trained readout networks and related important error statistics. Trained unit can contain cluster of the Feed Forward Networks or the Parallel Perceptron Networks|
+|ReadoutLayer|Class implements independent readout layer concept useable separatedly or together with reservoir computing preprocessing. Supports x-fold cross validation together with clustering of the trained readout units.|
 |StateMachine|The main component. Encaptulates independent NeuralPreprocessor and ReadoutLayer fuctionalities into the single logical unit.|