Detection of Signals from Noisy Chaotic Interference
نویسندگان
چکیده
On the basis of nonlinear dynamical modeling we investigate a chaos-based detector, which allows the extraction of signal frequencies in noisy chaotic interference.The detection scheme is tested by using both computer-generated chaotic data and real-life Lorenz-Sten£o (LS) chaotic circuit data respectively. The performance analysis demonstrates that signals hidden beneath the chaotic ambient noise £oor can be detected. By using automatic estimation of regularisation parameters for the training data in a radial basis function (RBF) neural network, it is found that the detection performance may be improved. Physically, this implies that a chaotic synchronization-based secure communication system can be successfully attacked by use of a chaos-based detector.
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