The present bibliography represents a comprehensive list of references on nonlinear system
identification and its applications in signal processing, communications, and biomedical …

In this paper a new class of nonlinear adaptive filters, consisting of a linear combiner
followed by a flexible memory-less function, is presented. The nonlinear function involved in …

In this paper two novel nonlinear cascade adaptive architectures, here called sandwich
models, suitable for the identification of general nonlinear systems are presented. The …

For the correlated input, the Volterra kernel-based least mean-square (LMS) algorithm in the
time-domain exhibits a slow learning rate caused by the large eigenvalue spread of the …

Due to the computational complexity of the Volterra filter, there are limitations on the
implementation in practice. In this paper, a novel adaptive joint process filter using pipelined …

This paper presents a new spline prioritization optimization adaptive filter with arctangent-
exponential hyperbolic cosine (SPOAF-ARC-EHC) to solve the high steady-state error in …

The paper presents a new model of noise cancellation using cascading of cascaded LMS
adaptive filters. The model has a combination of '2 N+ 1 2 N+ 1'LMS filters for N-stage of …

A broad class of nonlinear systems and filters can be modeled by the Volterra series
representation. However, its practical use in nonlinear system identification is sometimes …

A new nonlinear filter, which employs an adaptive spline function as the basis function is
designed in this paper. The input signal to this filter is used to generate suitable parameters …

In most practical applications, the major drawback for using adaptive Volterra filters is the
large number of coefficients to cope with. Several research works discussing strategies to …