文件名称：Automatic Modulation Classification
文件大小：1.71MB
文件格式：RAR
更新时间：2022-01-09 02:49:19
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This book includes the majority of the methods developed over the last two decades. The algorithms are systematically classified to five major categories: likelihood-based classifiers, distribution test-based classifiers, feature-based classifiers, machine learning-assisted classifiers, and blind modulation classifiers. For each type of automatic modulation classifier, the assumptions and system requirements are listed, and the design and implementation are explained through mathematical expressions, graphical illustrations and programming pseudo codes. Performance comparisons among several automatic modulation classifiers from each category are presented with both theoretical analysis and simulated numerical experiments.
【文件预览】：
Automatic Modulation Classification_ Principles, Algorithms and Applications [Zhu & Nandi 2015-02-16].pdf