This block models a Radial Basis Neural Network.
A Radial Basis Neural Network is composed by two NeuralNetworkLayer (HiddenLayer_... and OutputLayer_...). Everyone is specified by the following parameters:
- numNeurons: it specifies the number of neurons which compose the layer (it is also equal to the rows numer of the weight and bias matrix and to the number of outputs of the layer;
- numInputs: it specifies the number of inputs of the layer (it is also equal to the columns numer of the weight matrix;
- weightTable: it is the weight table of the layer ([Number of Neurons x Number of Inputs]);
- biasTable: it is the bias table of the layer ([Number of Neurons x 1]);
The activation function of the layers is fixed: the HiddenLayer uses a RadBas anctivation function and the OutputLayer uses a PureLin anctivation function.
To get the weight and bias table as modelica wants two different ways was used:
- using the extractData.m MatLab script, located in Utilities folder;
- using the DataFiles Dymola library.
Release Notes:
Generated at 2024-04-25T18:15:59Z
by OpenModelicaOpenModelica 1.22.3 using GenerateDoc.mos