Automatic Digital Signal Types Recognition Using SI-NN and HOS

— Recognition of digital signal type is an important topic for various applications. In this paper a method is presented that identifies different types of digital signals. This method utilizes a radial basis function neural network as the classifier which an evolutionary algorithm, i.e. swarm intelligence (SI), is used to construct it. As the features of signals, this method uses fourth and sixth and eighth order of moments and cumulants, i.e. a combination of higher orders of statistics (HOS). In conjunction with neural network it is used K-fold cross validation to improve the generalization ability. Experimental results indicate that this method has high percentage of the correct classification to discriminate different types of signal even at low SNRs. Keywords-component; Statistical pattern recognition, signal type classification, radial basis function neural network, swarm intelligence, cross validation, higher order moments, higher order cumulants.

• Type: Conference
• Year: 2007
• Where: ICC
• Authors: Ataollah Ebrahimzadeh, Mehrdad Ardebilipour, Alireza Movahedian
• Keywords: Communications, Digital Signals, Function Neural Network, ICC 2007, Radial Basis Function