Perceptron demo:

  perceptron.m		Perceptron learning demo: two-class discrimination.
  percep3d.m		Perceptron demo using 3D plot: shows decision plane

  PlotPats.m    	Helper function: plots training patterns.
  PlotPats3D.m		3d version
  PlotBoundary.m 	Helper function: plots decision boundary
  PlotBoundary3D.m	3d version
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LMS demos:

  lms.m			LMS learning demo: fitting a line.
  lms3d.m		LMS demo using 3D plot: shows decision plane
  parabolas.m		Graphs parabolic error curves in weight space for LMS.
  bowl.m		Shows weight gradient descent along error surface in
			  weight space, plotted in 3D.
  xordemo.m		XOR problem, with stochastic learning

  LmsPat.dat		Data file: input patterns for line fitting task.
  LmsAns.dat		Data file: desired output for each input.
  PlotLmsPats.m		Helper function: plot training patterns.
  PlotLmsFn.m		Helper function: plot the line defined by the
			  current weight values.
  tss.m			Helper function: total sum-squared error.

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Polynomial classifier demo:

  poly.m		Polynomial classifier trained by perceptron algorithm.
