Java-Scheme Laboratory

Constructor Detail

• VarianceICA

  public VarianceICA(Node node,
                     int inputs,
                     int outputs)

Method Detail

• getSourceModel

  public Model getSourceModel()

• setSourceModel

  public void setSourceModel(Model m)

• setInput

  public void setInput(Vec in)

  Description copied from interface: Model
  model should begin observing this vector

  Specified by:

  setInput in interface Model

• basisMatrix

  public Matrix basisMatrix()

• output

  public VVector output()

• error

  public VVector error()

• getSize

  public int getSize()

  Description copied from interface: Model
  return size of vector this model expects

  Specified by:

  getSize in interface Model

• setInferenceTask

  public void setInferenceTask(Task t)

• infer

  public void infer()

  Description copied from interface: Model
  should infer values latent variables

  Specified by:

  infer in interface Model

• compute

  public void compute()

  Description copied from interface: Model
  contract is that getEnergy and getGradient must return correct values for current x after infer and compute has been called, but not necessarily before. This is to give model an opportunity to cache values of energy and gradient to avoid repeated computations.

  Specified by:

  compute in interface Model

• getEnergy

  public double getEnergy()

  Description copied from interface: Model
  return E = -log p(x)

  Specified by:

  getEnergy in interface Model

• getGradient

  public double[] getGradient()

  Description copied from interface: Model
  return dE/dx

  Specified by:

  getGradient in interface Model

• run

  public void run()

  Specified by:

  run in interface Task

• dispose

  public void dispose()

  Specified by:

  dispose in interface Model

  Specified by:

  dispose in interface Task

  Overrides:

  dispose in class NamedTask

• functionx

  public Functionx functionx()

  Description copied from interface: Model
  This presents a more functional interface to the model so that it can be driven by an optimiser. See classes Functionx and MinimiserBase in package samer.maths.opt.

  Specified by:

  functionx in interface Model

• posterior

  public Functionx posterior()

• learnHebbian

  public Model.Trainer learnHebbian()

• learnLewickiSejnowski

  public Model.Trainer learnLewickiSejnowski()

• learnDecayWhenActive

  public Model.Trainer learnDecayWhenActive()