An Intelligent System for Classification of the Communication formats Using PSO

Text Automatic identification of digital signal types is of interest for both civil and military applications. This paper presents an efficient signal type identifier that includes a variety of digital signals. In this method, a combination of higher order moments (HOM) and higher order cumulants (HOC) are used as the features. A multi-layer perceptron neural network with SASS learning algorithm is proposed to determine the membership of the received signal. We have used swarm intelligence (SI) for feature selection in order to reduce the complexity of the classifier. Simulations results show that the proposed method has high performance for identification of different kinds of digital signal even at very low SNRs. This high efficiency is achieved with only seven features, which have been selected using particle swarm optimizer. Povzetek: Opisana je metoda za identifikacijo digitalnih signalov.