Neuron which calculates the output and performs learning. More...

#include <neuron.h>

Public Types
enum	WeightInitMethod { MAX_OUTPUT_RANDOM = 0, MAX_WEIGHT_RANDOM = 1, MAX_OUTPUT_CONST = 2, CONST_WEIGHTS = 3 }
	Constants how to init the weights in the neuron. More...

enum	ActivationFunction { LINEAR = 0, TANH = 1, RELU = 2, REMAXLU = 3, TANHLIMIT = 4 }
	Activation functions on offer LINEAR: linear unit, TANH: tangens hyperbolicus, RELU: linear rectifier, REMAXLU: as RELU but limits to one.

Public Member Functions
	Neuron (int _nInputs)
	Constructor. More...

	~Neuron ()
	Destructor Tidies up any memory allocations. More...

void	calcOutput ()
	Calculate the output of the neuron This runs the filters, activation functions, sum it all up.

void	doLearning ()
	Performs the learning Performs ICO learning in the neuron: pre * error. More...

void	doMaxDet ()
	Detects max of an input Switches the highest weight to 1 and the others to 0. More...

void	initWeights (double _max=1, int initBias=1, WeightInitMethod _wm=MAX_OUTPUT_RANDOM)
	Inits the weights in the neuron. More...

void	setActivationFunction (ActivationFunction _activationFunction)
	Sets the activation function. More...

double	dActivation ()
	Returns the output of the neuron fed through the derivative of the activation. More...

double	getMinWeightValue ()
	Minimum weight value. More...

double	getMaxWeightValue ()
	Maximum weight value. More...

double	getWeightDistanceFromInitialWeights ()
	Weight development. More...

double	getOutput ()
	Gets the output of the neuron. More...

double	getSum ()
	Gets the weighted sum of all inputs pre-activation function. More...

double	getWeight (int _index)
	Gets one weight. More...

void	setWeight (int _index, double _weight)
	Sets one weight. More...

void	setError (double _error)
	Sets the error in the neuron If the derivative is activated then the derivative of the error is calculated. More...

double	getError ()
	Gets the error as set by setError. More...

void	setInput (int _index, double _value)
	Sets one input. More...

double	getInput (int _index)
	Get the value at one input. More...

double	getBiasWeight ()
	Gets the bias weight. More...

void	setBiasWeight (double _biasweight)
	Sets the bias weight. More...

void	setBias (double _bias)
	Sets the bias input value. More...

void	setLearningRate (double _learningrate)
	Sets the learning rate. More...

void	setMomentum (double _momentum)
	Sets the momentum. More...

void	setDecay (double _decay)
	Sets the weight decay over time. More...

double	getDecay ()
	Gets the weight decay over time. More...

int	getNinputs ()
	Get the number of inputs to the neuron. More...

void	setGeometry (int _width, int _height)
	Tells the layer that it's been a 2D array originally to be a convolutional layer. More...

void	setMask (int x, int y, unsigned char c)
	Boundary safe manipulation of the convolution mask. More...

void	setMask (unsigned char c)
	Init the whole mask with a single value. More...

unsigned char	getMask (int x, int y)
	Boundary safe return of the mask in (x,y) coordinates. More...

unsigned char	getMask (int index)
	Boundary safe return of the mask in flat form. More...

double	getSumOfSquaredWeightVector ()
	Calculates the sum of the squared weight vector values. More...

double	getEuclideanNormOfWeightVector ()
	Calculates the Eucledian length of the weight vector. More...

double	getManhattanNormOfWeightVector ()
	Calculates the Manhattan length of the weight vector /return Manhattan length of the weight vector.

double	getInfinityNormOfWeightVector ()
	Calculates the Infinity norm of the vector. More...

double	getAverageOfWeightVector ()
	Calculates the average of the weight values. More...

void	normaliseWeights (double norm)
	Normalises the weights with a divisor. More...

void	saveInitialWeights ()
	Save the initial weights. More...

void	setDebugInfo (int _layerIndex, int _neuronIndex)
	Sets debug info populated from Layer. More...

void	setStep (long int _step)
	Sets the simulation step for debugging and logging. More...

Static Public Member Functions
static void *	calcOutputThread (void *object)
	Wrapper for thread callback for output calc. More...

static void *	doLearningThread (void *object)
	Wrapper for thread callback for learning. More...

static void *	doMaxDetThread (void *object)
	Wrapper for thread callback for maxdet. More...

Detailed Description

Neuron which calculates the output and performs learning.

Member Enumeration Documentation

◆ WeightInitMethod

enum Neuron::WeightInitMethod

Constants how to init the weights in the neuron.

Constructor & Destructor Documentation

◆ Neuron()

Neuron::Neuron ( int _nInputs )

Constructor.

Parameters

_nInputs Number of inputs to the Neuron

◆ ~Neuron()

Neuron::~Neuron ( )

Destructor Tidies up any memory allocations.

Member Function Documentation

◆ calcOutputThread()

static void* Neuron::calcOutputThread ( void * object )

inlinestatic

Wrapper for thread callback for output calc.

◆ dActivation()

double Neuron::dActivation ( )

Returns the output of the neuron fed through the derivative of the activation.

Returns: Result

◆ doLearning()

void Neuron::doLearning ( )

Performs the learning Performs ICO learning in the neuron: pre * error.

◆ doLearningThread()

static void* Neuron::doLearningThread ( void * object )

inlinestatic

Wrapper for thread callback for learning.

◆ doMaxDet()

void Neuron::doMaxDet ( )

Detects max of an input Switches the highest weight to 1 and the others to 0.

◆ doMaxDetThread()

static void* Neuron::doMaxDetThread ( void * object )

inlinestatic

Wrapper for thread callback for maxdet.

◆ getAverageOfWeightVector()

double Neuron::getAverageOfWeightVector ( )

Calculates the average of the weight values.

Returns: average of the weight values.

◆ getBiasWeight()

double Neuron::getBiasWeight ( )

inline

Gets the bias weight.

Returns: Bias weight value

◆ getDecay()

double Neuron::getDecay ( )

inline

Gets the weight decay over time.

Returns: The weight decay value. The larger the faster the weight decay.

◆ getError()

double Neuron::getError ( )

inline

Gets the error as set by setError.

Returns: The error value stored in the neuron

◆ getEuclideanNormOfWeightVector()

double Neuron::getEuclideanNormOfWeightVector ( )

inline

Calculates the Eucledian length of the weight vector.

Returns: Eucledian length of the weight vector.

◆ getInfinityNormOfWeightVector()

double Neuron::getInfinityNormOfWeightVector ( )

Calculates the Infinity norm of the vector.

/return Infinity norm of the vector.

◆ getInput()

double Neuron::getInput ( int _index )

inline

Get the value at one input.

Parameters

_index Index of the input

Returns: Returns the input value

◆ getMask() [1/2]

unsigned char Neuron::getMask ( int index )

inline

Boundary safe return of the mask in flat form.

Parameters

index Mask index.

Returns: The mask at the index: 0 = ignore underlying value, 1 = process underlying value.

◆ getMask() [2/2]

unsigned char Neuron::getMask	(	int	x,
		int	y
	)

Boundary safe return of the mask in (x,y) coordinates.

Parameters

x	Sets the mask value at coordinate x (0 .. width).
y	Sets the mask value at coordinate y (0 .. height).

Returns: The mask at x,y: 0 = ignore underlying value, 1 = process underlying value.

◆ getMaxWeightValue()

double Neuron::getMaxWeightValue ( )

Maximum weight value.

Returns: The maximum weight value in this neuron

◆ getMinWeightValue()

double Neuron::getMinWeightValue ( )

Minimum weight value.

Returns: The minimum weight value in this neuron

◆ getNinputs()

int Neuron::getNinputs ( )

inline

Get the number of inputs to the neuron.

Returns: The numer of inputs

◆ getOutput()

double Neuron::getOutput ( )

inline

Gets the output of the neuron.

Returns: The overall output of the neuron after the activation function

◆ getSum()

double Neuron::getSum ( )

inline

Gets the weighted sum of all inputs pre-activation function.

Returns: Weighted sum (linear)

◆ getSumOfSquaredWeightVector()

double Neuron::getSumOfSquaredWeightVector ( )

Calculates the sum of the squared weight vector values.

Returns: The squared weight vector values.

◆ getWeight()

double Neuron::getWeight ( int _index )

inline

Gets one weight.

Parameters

_index The input index

Returns: The weight value at one input and one filter

◆ getWeightDistanceFromInitialWeights()

double Neuron::getWeightDistanceFromInitialWeights ( )

Weight development.

Returns: Returns the Euclidean distance of the weights from their starting position

◆ initWeights()

void Neuron::initWeights	(	double	_max = `1`,
		int	initBias = `1`,
		WeightInitMethod	_wm = `MAX_OUTPUT_RANDOM`
	)

Inits the weights in the neuron.

Parameters

_max	Maximum value of the weights.
initBias	If one also the bias weight is initialised.
_wm	Method how to init the weights as defined by WeightInitMethod.

◆ normaliseWeights()

void Neuron::normaliseWeights ( double norm )

Normalises the weights with a divisor.

Parameters

norm	Divisor which normalises the weights.

◆ saveInitialWeights()

void Neuron::saveInitialWeights ( )

Save the initial weights.

This saves the initial weights for later comparisons. For internal use.

◆ setActivationFunction()

void Neuron::setActivationFunction ( ActivationFunction _activationFunction )

inline

Sets the activation function.

Parameters

_activationFunction Sets the activiation function according to ActivationFunction.

◆ setBias()

void Neuron::setBias ( double _bias )

inline

Sets the bias input value.

Parameters

_bias Bias value.

◆ setBiasWeight()

void Neuron::setBiasWeight ( double _biasweight )

inline

Sets the bias weight.

Parameters

_biasweight Bias value.

◆ setDebugInfo()

void Neuron::setDebugInfo	(	int	_layerIndex,
		int	_neuronIndex
	)

inline

Sets debug info populated from Layer.

Parameters

_layerIndex	The layer the neuron is in.
_neuronIndex	The index of the neuron in the layer.

◆ setDecay()

void Neuron::setDecay ( double _decay )

inline

Sets the weight decay over time.

Parameters

_decay The larger the faster the weight decay.

◆ setError()

void Neuron::setError ( double _error )

Sets the error in the neuron If the derivative is activated then the derivative of the error is calculated.

Parameters

_error Sets the error of the neuron.

◆ setGeometry()

void Neuron::setGeometry	(	int	_width,
		int	_height
	)

inline

Tells the layer that it's been a 2D array originally to be a convolutional layer.

_width * _height == nInputs. Otherwise an exception is triggered. The geometry entered here is then used in the mask operations so that every neuron is able to process a subset of the input space, for example an image and thus becomes a localised receptive field.

Parameters

_width	The width of the layer
_height	of the layer

◆ setInput()

void Neuron::setInput	(	int	_index,
		double	_value
	)

inline

Sets one input.

Parameters

_index	Index of the input.
_value	of the input.

◆ setLearningRate()

void Neuron::setLearningRate ( double _learningrate )

inline

Sets the learning rate.

Parameters

_learningrate The learning rate

◆ setMask() [1/2]

void Neuron::setMask	(	int	x,
		int	y,
		unsigned char	c
	)

Boundary safe manipulation of the convolution mask.

Sets the convolution mask using the geometry defined by setGeometry.

Parameters

x	Sets the mask value at coordinate x (0 .. width).
y	Sets the mask value at coordinate y (0 .. height).
c	Sets the mask: 0 = ignore underlying value, 1 = process underlying value.

◆ setMask() [2/2]

void Neuron::setMask ( unsigned char c )

Init the whole mask with a single value.

Parameters

c	Sets the mask for the whole array. 0 = ignore the entire input, 1 = process every input.

◆ setMomentum()

void Neuron::setMomentum ( double _momentum )

inline

Sets the momentum.

Sets the inertia of the learning.

Parameters

_momentum The new momentum

◆ setStep()

void Neuron::setStep ( long int _step )

inline

Sets the simulation step for debugging and logging.

Parameters

_step Current simulation step.

◆ setWeight()

void Neuron::setWeight	(	int	_index,
		double	_weight
	)

inline

Sets one weight.

Parameters

_index	The input index
_weight	The weight value

The documentation for this class was generated from the following files:

neuron.h
neuron.cpp

Public Types

Public Member Functions

Static Public Member Functions

Detailed Description

Member Enumeration Documentation

◆ WeightInitMethod

Constructor & Destructor Documentation

◆ Neuron()

◆ ~Neuron()

Member Function Documentation

◆ calcOutputThread()

◆ dActivation()

◆ doLearning()

◆ doLearningThread()

◆ doMaxDet()

◆ doMaxDetThread()

◆ getAverageOfWeightVector()

◆ getBiasWeight()

◆ getDecay()

◆ getError()

◆ getEuclideanNormOfWeightVector()

◆ getInfinityNormOfWeightVector()

◆ getInput()

◆ getMask() [1/2]

◆ getMask() [2/2]

◆ getMaxWeightValue()

◆ getMinWeightValue()

◆ getNinputs()

◆ getOutput()

◆ getSum()

◆ getSumOfSquaredWeightVector()

◆ getWeight()

◆ getWeightDistanceFromInitialWeights()

◆ initWeights()

◆ normaliseWeights()

◆ saveInitialWeights()

◆ setActivationFunction()

◆ setBias()

◆ setBiasWeight()

◆ setDebugInfo()

◆ setDecay()

◆ setError()

◆ setGeometry()

◆ setInput()

◆ setLearningRate()

◆ setMask() [1/2]

◆ setMask() [2/2]

◆ setMomentum()

◆ setStep()

◆ setWeight()