Summary
This paper proposes a new approach investigating the applicationof moment method to evaluate a set of candidate features and toselect an informative subset to be used as input data for a neuralnetwork classifier. The first step (pre-processing) of proposedmethod takes into account the discriminative properties ofinvariant krawtchouk moments. The second step (recognition) isachieved by using multilayer feedforward neural network(MFNN) as a classifier with the stochastic back propagation as alearning algorithm. Finite vectors obt ....etc

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Objective
Program in “LEX” to count number of Characters, Words, Lines.

%{
int nchar=0,nword=0,nline=0;
#include
%}
%%
\n {nline++;nchar++;}
+ {nword++;nchar+=yyleng;}
. {nchar++;}
%%
int main()
{
yylex();
printf(%d%d%d,nchar,nword,nline);
}
....etc

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