The radial basis function network-based autoregressive with exogenous inputs (RBF-ARX)
models have much more linear parameters than nonlinear parameters. Taking advantage of …

In our previous papers, fuzzy model identification methods were discussed. The bacterial
evolutionary algorithm for extracting fuzzy rule base from a training set was presented. The …

The aim of this chapter is to introduce background concepts in nonlinear systems
identification and control with artificial neural networks. As this chapter is just an overview …

The accuracy of classification and regression tasks based on data driven models, such as
Neural Networks or Support Vector Machines, relies to a good extent on selecting proper …

This study focuses on the finite-time extended dissipativity of delayed Takagi–Sugeno (T–S)
fuzzy neural networks (NNs). Based on the concept of extended dissipativity, this paper …

This contribution introduces a new digital predistorter to compensate serious distortions
caused by memory high power amplifiers (HPAs) which exhibit output saturation …

This paper presents a novel calculation of fuzzy exponent in the sigmoid functions for fuzzy
neural networks. The investigated fuzzy neural network applies fuzzy input signals and crisp …

In previous papers from the authors fuzzy model identification methods were discussed. The
bacterial algorithm for extracting fuzzy rule base from a training set was presented. The …

The design phase of B-spline neural networks is a highly computationally complex task.
Existent heuristics have been found to be highly dependent on the initial conditions …

Terrain-aided navigation technology estimates position information based on the terrain
elevation data, and corrects the inertial navigation system (INS) error. A terrain matching …