Title of article :
Signal Identification Using a New High Efficient Technique
Author/Authors :
Ebrahimzadeh, A university of mazandaran, بابلسر, ايران , Seyedin, S.A ferdowsi university of mashhad, مشهد, ايران
Abstract :
Automatic signal type identification (ASTI) is an important topic for both the civilian and military domains. Most of the proposed identifiers can only recognize a few types of digital signal and usually need high levels of SNRs. This paper presents a new high efficient technique that includes a variety of digital signal types. In this technique, a combination of higher order moments and higher order cumulants (up to eighth) are proposed as the effective features. A hierarchical support vector machine based structure is proposed as the classifier. In order to improve the performance of identifier, a genetic algorithm is used for parameters selection of the classifier. Simulation results show that the proposed technique is able to identify the different types of digital signal (e.g. QAM128, ASK8, and V29) with high accuracy even at low SNRs
Keywords :
Statistical pattern recognition , Signal identification , Support vector machine , Higher order moments, Higher order cumulants.
Journal title :
Iranian Journal of Electrical and Electronic Engineering(IJEEE)
Journal title :
Iranian Journal of Electrical and Electronic Engineering(IJEEE)