Abstract
A modulation process is required to transmit analog signals with higher quality. Modulation is the process of transporting the signal by another carrier signal. This study aims to process analog signals. Using 200 samples of each of the six types of analog modulation modules. Nowadays these are Amplitude Modulation (AM), Double Side Band (DSB), Upper Side Band (USB), Lower Side Band (LSB), Frequency Modulation (FM) and Phase Modulation(PM) respectively. In the study an intelligent clustering method has been developed. The 5th level Discrete Wavelet Transform (DWT), Norm Entropy and Energy properties of AM, DSB, USB, LSB, FM and PM analog modulated signals have been removed during feature extraction phase. The results have been compared using K-Means, k-Medoid and Fuzzy C Mean (FCM) algorithms using a feature vector of 6x2x1200 obtained at the feature extraction stage and carrying out smart intelligent clustering for recognition. The most successful result has been obtained with FCM of 85.75%.00
Highlights
T HE INFORMATION to be used in communication is not used where it is produced
Distinguishes Discrete Wavelet Transform (DWT) from other conventional modulation recognition methods is the use of different windowing techniques [9]
DWTs are used in applications such as astronomy, fingerprint verification, geophysics, internet traffic regulation, meteorology, computer graphics analysis, speech recognition [11]
Summary
T HE INFORMATION to be used in communication is not used where it is produced. Information may need to be moved to different locations. The process of transmitting a low frequency information from one place to another with a high frequency signal is called modulation. Using real human audio signals, a carrier-clustered intelligent clustering method has been developed for recognition using 200 samples from each of 6 kinds of analog modulation types. H. et al have used 5 kinds of modulation (Amplitude Modulation, Double Side Band Modulation, Frequency Modulation, Upper Single Band Modulation, Lower Single Band Modulation) for clustering process They compared performance using K-means, Fuzzy C-means, Mountain and Subtractive clustering methods [3]. E., made a strong feature in order to classify the targets created by the radar correctly He used pattern recognition methods to accomplish this purpose. A. et al have performed the modulation recognition process using Bayes decision rule method to classify analog modulated communication signals [5]. BALKAN JOURNAL OF ELECTRICAL & COMPUTER ENGINEERING, Vol 7, No 3, July 2019 the performance of algorithms by performing various tests on synthetic and real data sets by using partitioned clustering methods [8]
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