org.encog.mathutil.randomize

Class GaussianRandomizer

java.lang.Object

org.encog.mathutil.randomize.BasicRandomizer

org.encog.mathutil.randomize.GaussianRandomizer

All Implemented Interfaces:

Randomizer

public class GaussianRandomizer
extends BasicRandomizer

Generally, you will not want to use this randomizer as a pure neural network randomizer. More on this later in the description. Generate random numbers that fall within a Gaussian curve. The mean represents the center of the curve, and the standard deviation helps determine the length of the curve on each side. This randomizer is used mainly for special cases where I want to generate random numbers in a Gaussian range. For a pure neural network initializer, it leaves much to be desired. However, it can make for a decent randomizer. Usually, the Nguyen Widrow randomizer performs better. Uses the "Box Muller" method. http://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform Ported from C++ version provided by Everett F. Carter Jr., 1994

Constructor Summary

Constructors

Constructor and Description
GaussianRandomizer(double mean, double standardDeviation) Construct a Gaussian randomizer.

Method Summary

Methods

Modifier and Type	Method and Description
double	boxMuller(double m, double s) Compute a Gaussian random number.
double	randomize(double d) Generate a random number.

Methods inherited from class org.encog.mathutil.randomize.BasicRandomizer

getRandom, nextDouble, nextDouble, randomize, randomize, randomize, randomize, randomize, randomize, setRandom

Methods inherited from class java.lang.Object

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

Constructor Detail

GaussianRandomizer

public GaussianRandomizer(double mean,
                  double standardDeviation)

Construct a Gaussian randomizer. The mean, the standard deviation.

Parameters:

mean - The mean.

standardDeviation - The standard deviation.

Method Detail

boxMuller

public double boxMuller(double m,
               double s)

Compute a Gaussian random number.

Parameters:

m - The mean.

s - The standard deviation.

Returns:

The random number.

randomize

public double randomize(double d)

Generate a random number.

Parameters:

d - The input value, not used.

Returns:

The random number.