Nonlinear systems constituted by a zero-memory nonlinearity cascaded with linear filters can be identified by input-output cross correlation using a Gaussian input signal. The method is extended to complex systems through a pair of complex invariance theorems. The stated properties allow identifying the linear parts of systems characterized by magnitude/phase nonlinearities with the joint use of second- and third-order input-output moments. The method can be employed for a wide class of communication bandpass circuits when signals are represented by complex envelope
Algorithms for the identification of open and closed-loop nonlinear systems composed of linear dynam...
Correlation techniques for the identification of nonlinear systems are discussed in Chapter 1. The V...
Algorithms for the identification of open and closed-loop nonlinear systems composed of linear dynam...
Nonlinear systems constituted by a zero-memory nonlinearity cascaded with linear filters can be iden...
Abstract. Nonlinear behaviour appears in almost all digital commu-nication systems, such as satellit...
This thesis is concerned with the measurement of the characteristics of nonlinear systems by crossco...
Multiple-variance identification methods are based on the use of input signals with different powers...
The full text of this article is not available on SOAR. WSU users can access the article via IEEE Xp...
The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre no...
An identification algorithm for systems which can be represented by a nonlinear S m model is present...
Identification of nonlinear systems which can be represented by combinations of linear dynamic and s...
In this paper, we present a class of cascaded nonlinear models for complex-valued system identificat...
Bibliography: leaves 222-230xiv, 230 leaves : ill ; 30 cm.Thesis (Ph.D.)--University of Adelaide, De...
Journal ArticleAbstract-This paper is concerned with the blind identification of a class of bilinear...
The objective of this dissertation is to use neural network technology, in conjunction with second o...
Algorithms for the identification of open and closed-loop nonlinear systems composed of linear dynam...
Correlation techniques for the identification of nonlinear systems are discussed in Chapter 1. The V...
Algorithms for the identification of open and closed-loop nonlinear systems composed of linear dynam...
Nonlinear systems constituted by a zero-memory nonlinearity cascaded with linear filters can be iden...
Abstract. Nonlinear behaviour appears in almost all digital commu-nication systems, such as satellit...
This thesis is concerned with the measurement of the characteristics of nonlinear systems by crossco...
Multiple-variance identification methods are based on the use of input signals with different powers...
The full text of this article is not available on SOAR. WSU users can access the article via IEEE Xp...
The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre no...
An identification algorithm for systems which can be represented by a nonlinear S m model is present...
Identification of nonlinear systems which can be represented by combinations of linear dynamic and s...
In this paper, we present a class of cascaded nonlinear models for complex-valued system identificat...
Bibliography: leaves 222-230xiv, 230 leaves : ill ; 30 cm.Thesis (Ph.D.)--University of Adelaide, De...
Journal ArticleAbstract-This paper is concerned with the blind identification of a class of bilinear...
The objective of this dissertation is to use neural network technology, in conjunction with second o...
Algorithms for the identification of open and closed-loop nonlinear systems composed of linear dynam...
Correlation techniques for the identification of nonlinear systems are discussed in Chapter 1. The V...
Algorithms for the identification of open and closed-loop nonlinear systems composed of linear dynam...