Recursive identification of MIMO Wiener systems with general inputs

The paper concerns the identification of the multiple-input multiple-output (MIMO) Wiener system consisting of a linear subsystem followed by a static nonlinearity. Based on Fourier transform, the coefficient matrices of the linear subsystem is recursively estimated by stochastic approximation based principal component analysis (SABPCA) method with random inputs with possibly non-Gaussian distribution. The main contribution of the paper also consists in establishing convergence with probability one of the proposed algorithm to the true values. A numerical example is given to justify the theoretical analysis.