function tbxStruct=Demos
% DEMOS   Demo list for the Neural Network Toolbox

% Mark Beale, 11-5-97
% Copyright 1992-2000 The MathWorks, Inc.
% $Revision: 1.19 $

if nargout==0, demo toolbox; return; end

tbxStruct.Name='Neural Networks';
tbxStruct.Type='toolbox';

tbxStruct.Help= {
    ' The Neural Network Toolbox includes many    '
    ' kinds of powerful networks for solving  '
    ' problems including: '
    '    - function approximation, modeling,'
    '    - signal processing and prediction'
    '    - classification, and clustering.'
    ' '
    ' These tools are an essential part of many '
    ' applications, including engineering, finance,'
    ' medicine, and artificial intelligence.'
    ' '
    ' '
     };

tbxStruct.DemoList={
                'Simple neuron and transfer functions', 'nnd2n1',
                'Neuron with vector input', 'nnd2n2',
				...
                'Decision Boundaries', 'nnd4db',
                'Perceptron learning rule', 'nnd4pr',
                'Classification with a 2-input perceptron', 'demop1',
                'Outlier input vectors', 'demop4',
                'Normalized perceptron rule', 'demop5',
                'Linearly non-separable vectors', 'demop6',
				...
                'Pattern association showing error surface', 'demolin1',
                'Training a linear neuron', 'demolin2',
                'Linear classification system', 'nnd10lc',
                'Adaptive noise cancellation', 'demolin8',
                'Adaptive noise cancellation in airplane', 'nnd10nc',
                'Linear fit of nonlinear problem', 'demolin4',
                'Underdetermined problem', 'demolin5',
                'Linearly dependent problem', 'demolin6',
                'Too large a learning rate', 'demolin7',
				...
                'Generalization', 'nnd11gn',
                'Steepest descent backpropagation', 'nnd12sd1',
                'Momentum backpropagation', 'nnd12mo',
                'Variable learning rate backpropagation', 'nnd12vl',
                'Conjugate gradient backpropagation', 'nnd12cg',
                'Marquardt backpropagation', 'nnd12m',
				...
                'Radial basis approximation', 'demorb1',
                'Radial basis underlapping neurons', 'demorb3',
                'Radial basis overlapping neurons', 'demorb4',
                'GRNN function approximation', 'demogrn1',
                'PNN classification', 'demopnn1',
				...
                'Competitive learning', 'democ1',
                'One-dimensional self-organizing map', 'demosm1',
                'Two-dimensional self-organizing map', 'demosm2',
 				...
                'Learning vector quantization', 'demolvq1',
  				...
                'Hopfield two neuron design', 'demohop1',
                'Hopfield unstable equilibria', 'demohop2',
                'Hopfield three neuron design', 'demohop3',
                'Hopfield spurious stable points', 'demohop4',
  				...
                'Linear design (command-line)', 'applin1',
                'Adaptive linear prediction (command-line)', 'applin2',
                'Elman amplitude detection (command-line)', 'appelm1',
                'Character recognition (command-line)', 'appcr1',
                ...
                'Predictive control of a tank reactor (sim)','predcstr',
                'NARMA-L2 control of a magnet levitation system (sim)','narmamaglev',
                'Reference control of a robot arm (sim)','mrefrobotarm',
                ...
                'Other Neural Network Design textbook demos','nnd'};

