A B C D E G H I L M N O P S T

A

absoluteError - Variable in class backpropagation.Backpropagation
Summed absolute error on the components of the output vector.
alterWeights() - Method in class backpropagation.Backpropagation
Alteration of the network with Gaussian.

B

Backpropagation - class backpropagation.Backpropagation.
Implementation of the well-known backpropagation algorithm with optional number of layers.
Backpropagation() - Constructor for class backpropagation.Backpropagation
Hidden constructor of the class to be used in the loadNeuro static method.
Backpropagation(int, int[]) - Constructor for class backpropagation.Backpropagation
Basic constructor.
Backpropagation(int, int[], double, double, double, double, double, double) - Constructor for class backpropagation.Backpropagation
Creation of a new BackProp network with lots of parameters.

C

calmingRate - Variable in class backpropagation.Backpropagation
Calming rate of the learning rate: 1.0 means constant learning rate.

D

d1sigmoid(double) - Method in class backpropagation.Backpropagation
First derivative of the sigmoid function.

E

elasticity - Variable in class backpropagation.Backpropagation
Elasticity of the sigmoid function.
elasticityRate - Variable in class backpropagation.Backpropagation
Changing rate of the elasticity.

G

getCalmingRate() - Method in class backpropagation.Backpropagation
Returns the calming rate.
getElasticity() - Method in class backpropagation.Backpropagation
Returns the actual elasticity.
getElasticityRate() - Method in class backpropagation.Backpropagation
Returns the elasticity rate.
getLearningRate() - Method in class backpropagation.Backpropagation
Returns the actual learning rate.
getMomentum() - Method in class backpropagation.Backpropagation
Returns the momentum.
getTheta() - Method in class backpropagation.Backpropagation
Returns the theta.

H

hidden(int, int) - Method in class backpropagation.Backpropagation
Returns the output value of the jth hidden neuron in the ith layer.

I

init() - Method in class backpropagation.Backpropagation
Initialization of the network with random weights.

L

layers - Variable in class backpropagation.Backpropagation
Layers of the network.
learn(double[], double[]) - Method in class backpropagation.Backpropagation
Teaches the network according to the input-output value pair.
learningRate - Variable in class backpropagation.Backpropagation
Learning rate of the network.
loadNeuro(String, String) - Static method in class backpropagation.Backpropagation
Loads a previously learned network.

M

momentum - Variable in class backpropagation.Backpropagation
Constant determining the influence of the previous weight change on the actual.

N

numberOfLayers - Variable in class backpropagation.Backpropagation
Number of the layers, must be at least 2.
numberOfNeurons - Variable in class backpropagation.Backpropagation
Number of the neurons in layers, must be at least 1.

O

output(int) - Method in class backpropagation.Backpropagation
Returns network output of a given neuron.

P

propagate(double[]) - Method in class backpropagation.Backpropagation
Propagates the network input to get the output.

S

saveNeuro(String, String) - Method in class backpropagation.Backpropagation
Saves the learned network weights.
setCalmingRate(double) - Method in class backpropagation.Backpropagation
Sets the calming rate.
setElasticity(double) - Method in class backpropagation.Backpropagation
Sets the elasticity.
setElasticityRate(double) - Method in class backpropagation.Backpropagation
Sets the elasticity rate.
setLearningRate(double) - Method in class backpropagation.Backpropagation
Sets the learning rate.
setMomentum(double) - Method in class backpropagation.Backpropagation
Sets the momentum.
setTheta(double) - Method in class backpropagation.Backpropagation
Sets the theta.
sigmoid(double) - Method in class backpropagation.Backpropagation
Sigmoid function working in the (-1,1) interval.

T

theta - Variable in class backpropagation.Backpropagation
Threshold of the sigmoid function.
toString() - Method in class backpropagation.Backpropagation
String representation of the network.
A B C D E G H I L M N O P S T