NearNeural

Class SinusoidalThresholdModel

java.lang.Object

NearNeural.WeightedThresholdModel

NearNeural.SinusoidalThresholdModel

All Implemented Interfaces:

ThresholdingAlgorithm

public class SinusoidalThresholdModel
extends WeightedThresholdModel
implements ThresholdingAlgorithm

Creates a new sinusoidal thresholding algorithm.

Version:

0.2

Author:

Stephen Wattam

Field Summary

Fields inherited from class NearNeural.WeightedThresholdModel

k

Constructor Summary

Constructors

Constructor and Description
SinusoidalThresholdModel(double p_k) Creates a new sinusoidal function with a given steepness.

Method Summary

Methods

Modifier and Type	Method and Description
double	differentialValue(Edge[] edges) Returns the differential of the thresholding function.
boolean	validateInput(double input) Validates input against the applicable range for this thresholding algorithm.
double	value(Edge[] edges) Calculates Neuron value from all Edges and their source Neurons.

Methods inherited from class NearNeural.WeightedThresholdModel

getK, setK

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SinusoidalThresholdModel

public SinusoidalThresholdModel(double p_k)

Creates a new sinusoidal function with a given steepness.

Parameters:

p_k - The steepness value

Method Detail

value

public double value(Edge[] edges)

Calculates Neuron value from all Edges and their source Neurons.

Specified by:

value in interface ThresholdingAlgorithm

Parameters:

edges - All of this neuron's edges

Returns:

This Neuron's value

validateInput

public boolean validateInput(double input)

Validates input against the applicable range for this thresholding algorithm.

Specified by:

validateInput in interface ThresholdingAlgorithm

Parameters:

input - The value to check

Returns:

True if the value is applicable to run though without error

differentialValue

public double differentialValue(Edge[] edges)

Returns the differential of the thresholding function.

Specified by:

differentialValue in interface ThresholdingAlgorithm

Parameters:

edges - The edges that comprise the links this neuron has.

Returns:

The differential of the value