An Adaptive Chaotic Demodulator Based on Neural Network Strategy
一种基于神经网络策略的自适应混沌解调器

Chaotic modulation is an important spread spectrum (SS) technique among chaotic communications. Based on the merits of the good adaptability and the good convergence of a radial basis function (RBF) neural network, an adaptive chaotic demodulator is proposed in the light of a suggested adaptive learnng algorithm in this paper. The demodulator makes use of the good approximation capacity to a nonlinear dynamical system by the RBF network. It can reliably recover source information from SS signal received by a receiver with the on-line and adaptive modes. The simulation results by using the logistic chaotic system to modulate the different source signals demonstrate the relevant conclusions.