In this paper, the nonlinear lattice-Hammerstein filter and its properties are derived. It is shown that the error signals are orthogonal to the input signal and also backward errors of different stages are orthogonal to each other. Numerical results confirm all the theoretical properties of the lattice-Hammerstein structure.

The primary difficulty in the identification of Hammerstein nonlinear systems (a static memoryless nonlinear system in series with a dynamic linear system) is that the output of the nonlinear system (input to the linear system) is unknown. By employing the theory of affine projection, we propose a gradient-based adaptive Hammerstein algorithm with variable step-size which estimates the Hammerst...

InterSymbol Interference (ISI) of the radio propagation through channels is a major factor that limits the performance of mobile communication systems and can be compensated by equalization. One of the basic groups of equalizers is based on linear algorithms. In this paper, we propose the other method based on Hammerstein filter as a nonlinear memoryless blind equalizer. We have compared these ...

When using Bai’s method for estimating the coefficients of both the linear and nonlinear parts of a Hammerstein model, there is no guarantee that the resulting linear filter will be stable. To obtain a stable linear filter the well-known minimum phase correction can be used. However, if it used without some compensation in the nonlinear part, one obtains a Hammerstein model with no theoretical ...

In this paper a dynamic behavior model of analog to digital converters is proposed. The model is aimed for post correction in wideband applications. The suggested post correction method is a combination of look up tables and model based correction. The model consists of three components. The first is a component represented by a Hammerstein model; that is a static nonlinearity followed by a tim...

The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error ...

This article summarizes and extends the recently proposed concept of Significance-Aware (SA) filtering for nonlinear acoustic echo cancellation. The core idea of SA filtering is to decompose the estimation of the nonlinear echo path into beneficially interacting subsystems, each of which can be adapted with high computational efficiency. The previously proposed SA Hammerstein Group Models (SA-H...

There are parametric and non-parametric methods for adaptive Hammerstein system identification. The most commonly used method is the non-parametric. In reality, the linear subsystem of a Hammerstein system is not of finite impulse response and nonparametric adaptive algorithms require large matrices and therefore increase computational complexity. The objectives of this paper are to identify th...

Skeletal muscle force can be estimated using surface electromyographic (sEMG) signals. Usually, the sEMG location for the sensors is near the respective muscle motor unit points. Skeletal muscles generate a temporal and spatial distributed EMG signal, which causes cross talk between different sEMG signal sensors. In this paper, an array of three sEMG sensors is used to capture the information o...