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- W3155751388 abstract "Huge demand for bandwidth-critical applications (civilian and military) has been risen due to crowded spectrum. In last decade, a huge number of innovations are being done in communications. Automatic modulation classification (AMC) is one such innovation to enable higher transmission reliability and transmission rate by altering the modulation format according to channel characteristics. AMC is being extended to various applications, such as medical, speech recognition, software-defined radio (SDR), image processing and cognitive radio (CR). This paper discusses the study of various modulation techniques based on different approaches. In this work, different kinds of features and classifiers are presented, along with that their merits and demerits are also discussed. This work will guide researchers to select appropriate classifiers and features for their work." @default.
- W3155751388 created "2021-04-26" @default.
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- W3155751388 date "2021-01-01" @default.
- W3155751388 modified "2023-09-24" @default.
- W3155751388 title "Automatic Modulation Recognition Using Machine Learning Techniques: A Review" @default.
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- W3155751388 doi "https://doi.org/10.1007/978-981-16-0443-0_12" @default.
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