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## Uses of Class
org.neuroph.core.Neuron

Packages that use Neuron
org.neuroph.core | Provides base classes and basic building components for neural networks.
org.neuroph.nnet.comp | Provides components for the specific neural network models.
org.neuroph.nnet.comp.neuron | Provides various specific neuron types
org.neuroph.nnet.learning | Provides implementations of specific neural network learning algorithms.
org.neuroph.util | Provides various utility classes for creating neural networks, type codes, parsing vectors, etc.

Uses of Neuron in org.neuroph.core

Fields in org.neuroph.core declared as Neuron
`protected Neuron` | `Connection.fromNeuron` From neuron for this connection (source neuron).
`protected Neuron[]` | `Layer.neurons` Array of neurons (Neuron instances)
`protected Neuron` | `Connection.toNeuron` To neuron for this connection (target, destination neuron) This connection is input connection for to neuron.

Methods in org.neuroph.core that return Neuron
`Neuron` | `Connection.getFromNeuron()` Gets from neuron for this connection
`Neuron[]` | `NeuralNetwork.getInputNeurons()` Returns input neurons
`Neuron` | `Layer.getNeuronAt(int index)` Returns neuron at specified index position in this layer
`Neuron[]` | `Layer.getNeurons()` Returns array of neurons in this layer
`Neuron[]` | `NeuralNetwork.getOutputNeurons()` Returns output neurons
`Neuron` | `Connection.getToNeuron()` Gets to neuron for this connection

Methods in org.neuroph.core with parameters of type Neuron
`void` | `Neuron.addInputConnection(Neuron fromNeuron)` Adds input connection from specified neuron
`void` | `Neuron.addInputConnection(Neuron fromNeuron, double weightVal)` Adds input connection with the given weight, from given neuron
`void` | `Layer.addNeuron(int index, Neuron neuron)` Adds specified neuron to this layer,at specified index position
`void` | `Layer.addNeuron(Neuron neuron)` Adds specified neuron to this layer
`void` | `NeuralNetwork.createConnection(Neuron fromNeuron, Neuron toNeuron, double weightVal)` Creates connection with specified weight value between specified neurons
`Connection` | `Neuron.getConnectionFrom(Neuron fromNeuron)` Gets input connection from the specified neuron * @param fromNeuron neuron connected to this neuron as input
`boolean` | `Neuron.hasInputConnectionFrom(Neuron neuron)`
`boolean` | `Neuron.hasOutputConnectionTo(Neuron neuron)`
`int` | `Layer.indexOf(Neuron neuron)` Returns the index position in layer for the specified neuron
`void` | `Neuron.removeInputConnectionFrom(Neuron fromNeuron)` Removes input connection which is connected to specified neuron
`void` | `Layer.removeNeuron(Neuron neuron)` Removes neuron from layer
`void` | `Neuron.removeOutputConnectionTo(Neuron toNeuron)`
`void` | `Connection.setFromNeuron(Neuron fromNeuron)` Sets from neuron for this connection
`void` | `NeuralNetwork.setInputNeurons(Neuron[] inputNeurons)` Sets input neurons
`void` | `Layer.setNeuron(int index, Neuron neuron)` Sets (replace) the neuron at specified position in layer
`void` | `NeuralNetwork.setOutputNeurons(Neuron[] outputNeurons)` Sets output neurons
`void` | `Connection.setToNeuron(Neuron toNeuron)` Sets to neuron for this connection

Constructors in org.neuroph.core with parameters of type Neuron
`Connection(Neuron fromNeuron, Neuron toNeuron)` Creates a new connection between specified neurons with random weight
`Connection(Neuron fromNeuron, Neuron toNeuron, double weightVal)` Creates a new connection to specified neuron with specified weight value
`Connection(Neuron fromNeuron, Neuron toNeuron, Weight weight)` Creates a new connection to specified neuron with specified weight object

Uses of Neuron in org.neuroph.nnet.comp

Constructors in org.neuroph.nnet.comp with parameters of type Neuron
`DelayedConnection(Neuron fromNeuron, Neuron toNeuron, double weightVal, int delay)` Creates an instance of delayed connection to cpecified neuron and with specified weight

Uses of Neuron in org.neuroph.nnet.comp.neuron

Subclasses of Neuron in org.neuroph.nnet.comp.neuron
`class` | `BiasNeuron` Neuron with constant high output (1), used as bias
`class` | `CompetitiveNeuron` Provides neuron behaviour specific for competitive neurons which are used in competitive layers, and networks with competitive learning.
`class` | `DelayedNeuron` Provides behaviour for neurons with delayed output.
`class` | `InputNeuron` Provides input neuron behaviour - neuron with input extranaly set, which just transfer that input to output without change.
`class` | `InputOutputNeuron` Provides behaviour specific for neurons which act as input and the output neurons within the same layer.
`class` | `ThresholdNeuron` Provides behaviour for neurons with threshold.

Methods in org.neuroph.nnet.comp.neuron with parameters of type Neuron
`void` | `BiasNeuron.addInputConnection(Neuron fromNeuron)`
`void` | `BiasNeuron.addInputConnection(Neuron fromNeuron, double weightVal)`

Uses of Neuron in org.neuroph.nnet.learning

Methods in org.neuroph.nnet.learning with parameters of type Neuron
`protected double` | `BackPropagation.calculateHiddenNeuronError(Neuron neuron)` Calculates and returns the neuron's error (neuron's delta) for the given neuron param
`protected void` | `UnsupervisedHebbianLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `ResilientPropagation.updateNeuronWeights(Neuron neuron)` Calculate and sum gradients for each neuron's weight, the actual weight update is done in batch mode
`protected void` | `PerceptronLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron In addition to weights change in LMS it applies change to neuron's threshold
`protected void` | `OutstarLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `OjaLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `MomentumBackpropagation.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron for the back propagation with momentum factor
`protected void` | `LMS.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron It iterates through all neuron's input connections, and calculates/set weight change for each weight using formula deltaWeight = learningRate * neuronError * input where neuronError is difference between desired and actual output for specific neuron neuronError = desiredOutput[i] - actualOutput[i] (see method SuprevisedLearning.calculateOutputError)
`protected void` | `InstarLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `GeneralizedHebbianLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `BinaryHebbianLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `AntiHebbianLearning.updateNeuronWeights(Neuron neuron)` This method implements weights update procedure for the single neuron
`protected void` | `SupervisedHebbianLearning.updateNeuronWeights(Neuron neuron, double desiredOutput)` This method implements weights update procedure for the single neuron

Uses of Neuron in org.neuroph.util

Methods in org.neuroph.util that return Neuron
`static Neuron` | `NeuronFactory.createNeuron(NeuronProperties neuronProperties)` Creates and returns neuron instance according to the given specification in neuronProperties.

Methods in org.neuroph.util with parameters of type Neuron
`static void` | `ConnectionFactory.createConnection(Neuron fromNeuron, Neuron toNeuron)` Creates connection between two specified neurons
`static void` | `ConnectionFactory.createConnection(Neuron fromNeuron, Neuron toNeuron, double weightVal)` Creates connection between two specified neurons
`static void` | `ConnectionFactory.createConnection(Neuron fromNeuron, Neuron toNeuron, double weightVal, int delay)`
`static void` | `ConnectionFactory.createConnection(Neuron fromNeuron, Neuron toNeuron, Weight weight)` Creates connection between two specified neurons

Constructor parameters in org.neuroph.util with type arguments of type Neuron
`NeuronProperties(Class<? extends Neuron> neuronClass)`
`NeuronProperties(Class<? extends Neuron> neuronClass, Class<? extends InputFunction> inputFunctionClass, Class<? extends TransferFunction> transferFunctionClass)`
`NeuronProperties(Class<? extends Neuron> neuronClass, Class<? extends TransferFunction> transferFunctionClass)`
`NeuronProperties(Class<? extends Neuron> neuronClass, TransferFunctionType transferFunctionType)`

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