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Automatic Recognition of Analog Modulated Signals Using Artificial Neural Networks
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作者 Jide Julius Popoola Rex Van Olst 《Computer Technology and Application》 2011年第1期29-35,共7页
This paper presents work on modulated signal recognition using an artificial neural network (ANN) developed using the Python programme language. The study is basically on the analysis of analog modulated signals. Fo... This paper presents work on modulated signal recognition using an artificial neural network (ANN) developed using the Python programme language. The study is basically on the analysis of analog modulated signals. Four of the best-known analog modulation types are considered namely: amplitude modulation (AM), double sideband (DSB) modulation, single sideband (SSB) modulation and frequency modulation (FM). Computer simulations of the four modulated signals are carried out using MATLAB. MATLAB code is used in simulating the analog signals as well as the power spectral density of each of the analog modulated signals. In achieving an accurate classification of each of the modulated signals, extensive simulations are performed for the training of the artificial neural network. The results of the study show accurate and correct performance of the developed automatic modulation recognition with average success rate above 99.5%. 展开更多
关键词 Automatic modulation recognition modulation schemes features extraction key artificial neural network (ANN).
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