Digital-signal-type identification using an efficient identifier

Authors:
Ataollah Abrahamzadeh;Seyed Alireza Seyedin;Mehdi Dehghan
Affiliations:
Faculty of Electrical and Computer Engineering, Noshirvani Institute of Technology, Mazandauan University, Babol, Iran;Faculty of Electrical Engineering, Department of Electrical Engineering, Ferdowsi University of Mashad, Mashad, Iran;Faculty of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2007

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Abstract

Automatic digital-signal-type identification plays an important role for various applications. This paper presents a highly efficient identifier (technique) that identifies a variety of digital signal types. In this technique, a selected number of the higher-order moments and the higher-order cumulants up to eighth are utilized as the effective features. A hierarchical support-vector-machine-(SVMs) based structure is proposed for multiclass classification. A genetic algorithm is proposed in order to improve the performance of the identifier. Genetic algorithm selects the suitable parameters of SVMs that are used in the structure of the classifier. Simulation results show that the proposed identifier has high performance for identification of the considered digital signal types even at very low SNRs.