/// <summary>
/// Initializes a new instance of the <see cref="ActivationNetwork"/> class.
/// </summary>
///
/// <param name="function">Activation function of neurons of the network.</param>
/// <param name="inputsCount">Network's inputs count.</param>
/// <param name="neuronsCount">Array, which specifies the amount of neurons in
/// each layer of the neural network.</param>
///
/// <remarks>The new network is randomized (see <see cref="ActivationNeuron.Randomize"/>
/// method) after it is created.</remarks>
///
public ActivationNetwork( IActivationFunction function, int inputsCount, params int[] neuronsCount )
: base( inputsCount, neuronsCount.Length )
{
// create each layer
for ( int i = 0; i < layers.Length; i++ )
{
layers[i] = new ActivationLayer(
// neurons count in the layer
neuronsCount[i],
// inputs count of the layer
( i == 0 ) ? inputsCount : neuronsCount[i - 1],
// activation function of the layer
function );
}
}
/// <summary>
/// Initializes a new instance of the <see cref="ActivationNetwork"/> class.
/// </summary>
///
/// <param name="function">Activation function of neurons of the network.</param>
/// <param name="inputsCount">Network's inputs count.</param>
/// <param name="neuronsCount">Array, which specifies the amount of neurons in
/// each layer of the neural network.</param>
///
/// <remarks>The new network is randomized (see <see cref="ActivationNeuron.Randomize"/>
/// method) after it is created.</remarks>
///
public ActivationNetwork(IActivationFunction function, int inputsCount, params int[] neuronsCount)
: base(inputsCount, neuronsCount.Length)
{
// create each layer
for (int i = 0; i < layers.Length; i++)
{
layers[i] = new ActivationLayer(
// neurons count in the layer
neuronsCount[i],
// inputs count of the layer
(i == 0) ? inputsCount : neuronsCount[i - 1],
// activation function of the layer
function);
}
}