This paper extends blind single-input single-output (SISO) Volterra-system identification
from the second-order statistics (SOSs) domain into the third-order statistics domain. For the …

This paper is concerned with blind identification for single‐input single‐output Volterra
systems with finite order and memory with the second‐order and the third‐order statistics …

In this correspondence, closed-form expressions for the blind identification of linear-
quadratic Volterra systems are established. The system is excited by a complex valued …

A novel approach to estimate blindly the kernels of a Volterra nonlinear system up to the
third order is proposed. The system is excited by an unobservable iid random sequence …

This paper reviews the basic identifiability conditions and identification methods for blind
system identification. This review focuses on the exploitation of the second-order statistics of …

Quadratic non‐linear systems are widely used in various engineering fields such as signal
processing, system filtering, predicting and identification. Some conditions to blindly …

The blind identification of a special class of nonlinear system is pursued in this paper. In
particular a genetic algorithm is developed for blind identification of quadratic Volterra model …

We show that a finite impulse response and multi-input-multi-output (FIR-MIMO) system with
colored input is blindly identifiable up to a permutation and scaling using the second order …

This paper presents a second-order statistics based method for blind identification of non-
minimum phase single-input–single-output (SISO) auto-regression moving-average (ARMA) …

In many real-world situations, man-made signals such as those encountered in rotating
machines, communications, telemetry, radar, and sonar systems are nonstationary and very …