Maximum likelihood least squares identification method for input nonlinear finite impulse response moving average systems

According to the maximum likelihood principle, a maximum likelihood least squares identification method is presented for input nonlinear finite impulse response moving average (IN-FIR-MA) systems (e.g., Hammerstein FIR-MA systems). The simulation results indicate that the proposed algorithm is effective.