ca.nengo.math

Interface LinearApproximator

All Superinterfaces:

java.lang.Cloneable, java.io.Serializable

All Known Implementing Classes:

CompositeApproximator, GradientDescentApproximator, IndependentDimensionApproximator, WeightedCostApproximator

public interface LinearApproximator
extends java.io.Serializable, java.lang.Cloneable

Finds coefficients on a set of functions so that their linear combination approximates a target Function. In other words, finds a_i so that sum(a_i * f_i(x)) roughly equals t(x) in some sense, where f_i are the functions to be combined and t is a target function, both over some range of the variable x.

Can be used to find decoding vectors and synaptic weights.

Method Summary

Methods

Modifier and Type	Method and Description
LinearApproximator	clone()
float[]	findCoefficients(Function target) Note: more information is needed than the arguments provide (for example the functions that are to be combined to estimate the target).
float[][]	getEvalPoints()
float[][]	getValues()

Method Detail

findCoefficients

float[] findCoefficients(Function target)

Note: more information is needed than the arguments provide (for example the functions that are to be combined to estimate the target). These other data are object properties. This enables re-use of calculations based on these data, for estimating multiple functions.

Parameters:

target - Function to approximate

Returns:

coefficients on component functions which result in an approximation of the target

clone

LinearApproximator clone()
                         throws java.lang.CloneNotSupportedException

Returns:

Valid clone

Throws:

java.lang.CloneNotSupportedException - if clone can't be made

getEvalPoints

float[][] getEvalPoints()

Returns:

Points at which target functions are evaluated. Each row (or float[]) corresponds to a single evaluation point. These points should usually be uniformly distributed, because the sum of error at these points is treated as an integral over the domain of interest.

getValues

float[][] getValues()

Returns:

The values of component functions at the evaluation points. The first dimension makes up the list of functions, and the second the values of these functions at each evaluation point.