An expert Discrete Wavelet Adaptive Network Based Fuzzy Inference System for digital modulation recognition

Authors:
Engin Avci;Davut Hanbay;Asaf Varol
Affiliations:
Firat University, Department of Electronic and Computer Education, 23119 Elazig, Turkey;Firat University, Department of Electronic and Computer Education, 23119 Elazig, Turkey;Firat University, Department of Electronic and Computer Education, 23119 Elazig, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2007

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Abstract

This paper presents a comparative study of implementation of feature extraction and classification algorithms based on discrete wavelet decompositions and Adaptive Network Based Fuzzy Inference System (ANFIS) for digital modulation recognition. Here, in first stage, 20 different feature extraction methods are generated by separately using Daubechies, Biorthogonal, Coiflets, Symlets wavelet families. In second stage, the performance comparison of these feature extraction methods is performed by using a new Expert Discrete Wavelet Adaptive Network Based Fuzzy Inference System (EDWANFIS). The digital modulated signals used in this experimental study are ASK8, FSK8, PSK8, QASK8. EDWANFIS structure consists of two parts. The first part is Discrete Wavelet Transform (DWT)-adaptive wavelet entropy and Adaptive Network Based Fuzzy Inference System for Automatic Digital Modulation Recognition (ADMR). The performance of this comparison system is evaluated by using total 800 digital modulated signals for each of these feature extraction methods. The performance comparison of these features extraction methods and the advantages and disadvantages of the methods are examined.