A Novel Classification and Identification Scheme of Emitter Signals Based on Ward’s Clustering and Probabilistic Neural Networks with Correlation Analysis

Algorithm 3

Identification algorithm.

	Input: The training samples , label matrix .
	Samples to be identified .
	Output: is the element of the class k.
	Normalize , ;
	Create PNN model by using and ;
	Adjust the dimension of to make it consistent with the ;
	Determining sequences and ;
	Compute fitting curves , ;
	Create feature sequences ;
	Compute , and if , then
	Put the into the trained PNN;
	else
	does not belong to any class;
	End: Identification algorithm.