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The Improvement and Application of Fuzzy Neural Network in Communication Signal Identification

In recent years, communication signal identification become a new issue in the field of communication reconnaissance, which is very important in the security of communication system and network, radio monitoring, cognitive radio, communication countermeasure and so on. So, in this paper, it provides a new approach for the recognition of communication signal. This approach combines evidence theory with fuzzy theory to build fuzzy evidence inference rules and learns with neural network, which can eliminate uncertainty, fuzziness and increase recognition rate. The simulation result shows that the new approach can cope with problems of different complexity, and provides much higher recognition rate.