Identification method for m-ary frequency shift keying signals based on adaptive neural-fuzzy inference system (ANFIS) and discrete wavelet transform
Global Proceedings Repository
View Archive Info| Field | Value | |
| Title |
Identification method for m-ary frequency shift keying signals based on adaptive neural-fuzzy inference system (ANFIS) and discrete wavelet transform
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| Creator |
Hadi A. Hamed
Sattar B. Sadkhan-SMIEEE Ashwaq Q. Hameed |
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| Description |
Automatic modulation identification (AMI) is the ability to classify the modulated signals of an arbitrary modulation schemes. The extension of digitally modulated signal applications are continuous to grow which gives the AMI high importance for proper selection of demodulators, interference identification, signal confirmation etc. This paper presents a study of feature extraction and a classifier for M-ary frequency shift keying (MFSK) based on 4th, 6th and 8th order moment of discrete wavelet transform (DWT) as an extracted feature and Adaptive Neural-Fuzzy Inference System (ANFIS) as a classifier. Haar type of DWT are selected, MATLAB program are designed to perform the reduction of number of extracted features as well as classification processes. The M-ary signals are 2FSK, 4FSK, and 8FSK. MFSK signals are generated and the features are extracted for a large set of numerically generated signals. The proposed identification method has a high performance, flexible for identify M-ary FSK signals when the signals are corrupted with additive white Gaussian noise (AWGN) at 0dB, 5dB, and 10 dB signal to noise ratio.
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| Publisher |
Int'l Conference on Change, Innovation, Informatics and Disrurptuive Technology
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| Contributor |
—
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| Date |
2016-12-17 20:54:21
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| Type |
Peer-reviewed Paper
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| Format |
application/pdf
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| Identifier |
http://proceedings.sriweb.org/repository/index.php/ICCIIDT/icciidtt_london/paper/view/21
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| Source |
Int'l Conference on Change, Innovation, Informatics and Disrurptuive Technology; ICCIIDT London - UK
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| Language |
en
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| Rights |
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