A response approximation method for stochastically excited, nonlinear, dynamic systems is presented. Herein, the output of the nonlinear system is approximated by a finite-order Volterra series. The original nonlinear system is replaced by a bilinear system in order to determine the kernels of this Volterra series. The parameters of the bilinear system are determined by minimizing the differenc...

Detecting nonlinear correlations between time series presents a hard problem for data analysis. We present a generative statistical modeling method for detecting nonlinear generalized synchronization. Truncated Volterra series are used to approximate functional interactions. The Volterra kernels are modeled as linear combinations of basis splines, whose coefficients are estimated via l(1) and l...

We consider baseband equivalent representation of transmission circuits, in the form of a nonlinear dynamical system S in discrete time (DT) defined by a series interconnection of a phase-amplitude modulator, a nonlinear dynamical system F in continuous time (CT), and an ideal demodulator. We show that when F is a CT Volterra series model, the resulting S is a series interconnection of a DT Vol...

New results about the bound characteristics of both the generalized frequency response functions (GFRFs) and the output frequency response for the NARX (Nonlinear AutoRegressive model with eXogenous input) model are established. It is shown that the magnitudes of the GFRFs and the system output spectrum can all be bounded by a polynomial function of the magnitude bound of the first order GFRF, ...

The multiple-input multiple-output (MIMO) performance of the modulated scattering antenna array (MSAA) is analyzed numerically for the first time in indoor environment based on an approach to hybridization of the Volterra series method and method of moments (MoM) in this letter. Mutual coupling effect between the Modulated scattering element (MSE) and the normal antenna element is also consider...

A response approximation method for stochastically excited, nonlinear, dynamic systems is presented. Herein, the output of the nonlinear system is approximated by a finite-order Volterra series. The original nonlinear system is replaced by a bilinear system in order to determine the kernels of this Volterra series. The parameters of the bilinear system are determined by minimizing in a statisti...