It is significant to fit a Gaussian function with the observation data for artificial intelligence or
other engineering fields. Considering the influence of noises, this article proposes a …

This article studies the parameter estimation to the system response from the discrete
measurement data. By constructing the dynamical rolling cost functions and using the …

The parameter estimation methods for the nonlinear exponential autoregressive model are
investigated in this paper. We develop a forgetting factor gradient parameter estimation …

The sine signals are widely used in signal processing, communication technology, system
performance analysis and system identification. Many periodic signals can be transformed …

It is well-known that the stochastic gradient (SG) identification algorithm has poor
convergence rate. In order to improve the convergence rate, we extend the SG algorithm …

This paper derives the multi-innovation extended stochastic gradient algorithm for controlled
autoregressive moving average models by expanding the scalar innovation to an innovation …

This paper studies the parameter estimation algorithms of a finite impulse response system
with colored noise. To suppress the negative effects of the colored noises, a novel gradient …

Variable‐gain nonlinearity is a piecewise‐linear characteristic to describe the process with
different gains in different input regions. This article studies the parameter estimation issue …

For pseudo-linear regression identification models corresponding output error systems with
colored measurement noises, a difficulty of identification is that there exist unknown inner …

This article focuses on the parameter estimation for a class of nonlinear systems, that is,
multi‐input single‐output or two‐input single‐output Hammerstein finite impulse response …