Behavioral economics tells us that emotions can profoundly affect individual behavior and
decision-making. Does this also apply to societies at large, ie can societies experience …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

The motor unit action potentials (MUPs) in an electromyographic (EMG) signal provide a
significant source of information for the assessment of neuromuscular disorders. Since …

This paper presents a new on-line algorithm for creating a self-organizing fuzzy neural
network (SOFNN) from sample patterns to implement a singleton or Takagi-Sugeno (TS) …

Deep belief network (DBN) is an efficient learning model for unknown data representation,
especially nonlinear systems. However, it is extremely hard to design a satisfactory DBN …

Nonlinear system modeling plays an important role in practical engineering, and deep
learning-based deep belief network (DBN) is now popular in nonlinear system modeling and …

In this paper, a self-organizing cascade neural network (SCNN) with random weights is
proposed for nonlinear system modeling. This SCNN is constructed via simultaneous …

In this paper, a novel fuzzy neural network termed as dynamic parsimonious fuzzy neural
network (DPFNN) is proposed. DPFNN is a four layers network, which features coalescence …

Three new learning algorithms for Takagi-Sugeno-Kang fuzzy system based on training
error and genetic algorithm are proposed. The first two algorithms are consisted of two …

This paper presents a direct self-structuring adaptive fuzzy control (DSAFC) scheme for
affine nonlinear single-input–single-output systems. We show that the only restriction on the …