1. Functions of the Network Structure Estimation Program
 a. Reads a training data file
 b. Requests a minimum acceptable training error 
    from the user,
 c. Requests a maximum number of iterations from the user.
    A typical number is 10.
 d. Estimates the required network structure for an MLP to attain 
    the desired classification error percentage
 e. Notifies user if the network will generalize or memorize

2. Example Run of the Network Structure Estimation Program
 a. Go to the "Batch Processing" option and press <ret>
 b. Observe the parameter file with commented keyboard responses;

Gls           ! input training data filename
4             ! number of inputs per pattern 
1             ! number of outputs per pattern 
.001          ! maximum acceptable mean-square training error
8             ! maximum allowable number of iterations

    Here, we will estimate the required size of an MLP for 
    predicting chaotic time series created by the Mackey-Glass 
    delay-difference equation, 
    (Ref. Lapedes, A. & Farber, R.1987 Nonlinear Signal processing using 
    Networks : Prediction & System modelling,  Tech. Rep. LA-UR-87-2662, 
    Los Alamos National Laboratory, Los Alamos, NM.)
 c. Exit the DOS editor and observe the program running
 d. Go to the "Examine Program Output" option and press <ret>
 e. The program predicts that a network with 9 hidden units can be
    trained with a MSE of .000987, and that networks with the proposed
    structure should successfully generalize
 f. You can run this program on your own data, simply by editing the 
    parameter file in the "batch Run" option.
