A Novel Modulation Classification Approach Using Gabor Filter Network
Joint Authors
Qureshi, Ijaz Mansoor
Malik, Aqdas Naveed
Ghauri, Sajjad Ahmed
Cheema, Tanveer Ahmed
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-13
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network.
Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN).
The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64.
The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part.
The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm.
The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel.
American Psychological Association (APA)
Ghauri, Sajjad Ahmed& Qureshi, Ijaz Mansoor& Cheema, Tanveer Ahmed& Malik, Aqdas Naveed. 2014. A Novel Modulation Classification Approach Using Gabor Filter Network. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1050471
Modern Language Association (MLA)
Ghauri, Sajjad Ahmed…[et al.]. A Novel Modulation Classification Approach Using Gabor Filter Network. The Scientific World Journal No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1050471
American Medical Association (AMA)
Ghauri, Sajjad Ahmed& Qureshi, Ijaz Mansoor& Cheema, Tanveer Ahmed& Malik, Aqdas Naveed. A Novel Modulation Classification Approach Using Gabor Filter Network. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1050471
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050471