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Support vector machines (SVMs) deal with challenging classification problems. One such a challenge is to classify the modulation type of a signal transmitted over High frequency (HF) band. The noise distribution in this band has time varying nature. SVM can mitigate these variations with correct choice of features and kernel functions. This paper presents a feature-based classification method utilizing...
High frequency (HF) band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC) is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR). Such a method has two main...
Automatic Modulation Classification (AMC) is the process of classifying the received signals without prior information. This process is an intermediate step between signal detection and demodulations. It serves both military and civilian applications, such as spectrum monitoring and general-purpose universal demodulators. In this paper, we propose a Decision Tree (DT) algorithm to classify a wide...
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