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    Signature recogniation rbf(radial basis function) neural network at matlab

    I have got two questions
    hi i have been working about signature recocniation system in matlab.I decide to classify with rbfnn(radial basis function neural network) .I can do %60 in accuracy.The system must to work higher accuracy.Number of educational data is 728.(28*26).There are 28 persons signature.Each person has got 26 signatures.Number of test signature is 280.(28*10).There are 28 persons in signature recogniation system.Each person has got 10 signatures.

    1-Which spread value i can chose?
    eg = 0.001; % sum-squared error goal
    sc = 11;    % spread constant
    newrb(X,T,GOAL,SPREAD,MN,DF) takes these arguments,
    X - RxQ matrix of Q input vectors.
    T - SxQ matrix of Q target class vectors.
    GOAL - Mean squared error goal, default = 0.0.
    SPREAD - Spread of radial basis functions, default = 1.0.
    MN - Maximum number of neurons, default is Q.
    DF - Number of neurons to add between displays, default = 25.
    and returns a new radial basis network.

    The larger that SPREAD is the smoother the function approximation
    will be. Too large a spread means a lot of neurons will be
    required to fit a fast changing function. Too small a spread
    means many neurons will be required to fit a smooth function,
    and the network may not generalize well. Call newrb with
    different spreads to find the best value for a given problem.
    Here we design a radial basis network given inputs X and targets T.
         X = [1 2 3];
         T = [2.0 4.1 5.9];
         net = newrb(X,T);
         Y = net(X)
    my code is
    eg = 0.001; % sum-squared error goal
    sc = 11;    % spread constant
    net = newrb(input,target,eg,sc);
    There is'nt any parameters set nember of epochs
    How can i set number of epochs?

    Please help me...
    Last edited by bigdogguru; 8th January 2015 at 03:10. Reason: Added CODE or SYNTAX Tags

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