Given the nonlinear channel, the online blind equalization algorithm for Quadrature Amplitude Modulation (QAM) signals based on the prediction principle via the Complex Echo State Network(C-ESN) is proposed. The traditional linear prediction error filter is replaced by the C-ESN with good nonlinear mapping ability, and the minimum prediction error is attained by the Kalman filter(KF). After then, the amplitude and phase are adjusted in sequence. Simulation results show that the proposed algorithm can effectively reduce the distortion of the transmitted QAM signals caused by nonlinear channels. Compared with other prediction principle-based blind equalization algorithms and the traditional cost function based ESN blind equalization algorithm, it has lower mean square error and faster convergence speed.

For nonlinear channels, we propose a new blind equalization method for chaotic signals based on echo state network( ESN) and Kalman filter(KF) in this letter. Using the shortterm predictability of chaotic signals, ESN, a new feedback neural network, is used to approximate unknown chaotic maps and predict the output of the equalizer. Furthermore, KF combined with the finite impulse response(FIR) is used as the equalizer in this letter, and its parameters are adjusted by minimizing the prediction error of ESN. Simulation results show that compared with other blind equalization methods for chaotic signals, the proposed method has the advantages of smaller mean square error and faster convergence rate, and is suitable for strong nonlinear channels.

In this paper, we investigate a novel synchronization method, which consists of n(n ≥ 2) cascade‐coupled chaotic systems. Furthermore, as the number of chaotic systems decreases from n to 2, the proposed synchronization will transform into bidirectional coupling synchronization. Based on Lyapunov stability theory, a general criterion is proposed for choosing the appropriate coupling parameters to ensure cascading synchronization. Moreover, 4 Lü systems are taken as an example and the corresponding numerical simulations demonstrate the effectiveness of our idea.