This paper studies the generalized time-varying systems identification problem by means of
a time-varying parameter expression. The basic idea is to propose an extended stochastic …

The Kalman filter (KF) is a popular state estimation technique that is utilized in a variety of
applications, including positioning and navigation, sensor networks, battery management …

This article is aimed to study the modeling problems of combinational signals or periodic
signals. To overcome the computation complexity of modeling the signals with plenty of …

This paper considers the parameter estimation problem of nonlinear models, which are
related to the impulse or step response functions of linear time-invariant (LTI) dynamical …

This paper focuses on the identification of a multivariable controlled autoregressive-like
(CAR-like) system. A joint identification algorithm of stochastic gradient and least squares is …

With the development of advanced information and intelligence technologies, precision
agriculture has become an effective solution to monitor and prevent crop pests and …

For a dual‐rate sampled‐data stochastic system with additive colored noise, a dual‐rate
identification model is obtained by using the polynomial transformation technique, which is …

This paper mainly investigates the issue of parameter identification for the fractional‐order
input nonlinear output error autoregressive (IN‐OEAR) model. In order to avoid the problem …

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 …

Due to the nonlinear modeling capabilities, deep learning prediction networks have become
widely used for smart agriculture. Because the sensing data has noise and complex …