Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

In this paper, we develop an online sequential learning algorithm for single hidden layer
feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a …

A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …

One of the open problems in neural network research is how to automatically determine
network architectures for given applications. In this brief, we propose a simple and efficient …

Radial basis function (RBF) networks have advantages of easy design, good generalization,
strong tolerance to input noise, and online learning ability. The properties of RBF networks …

We introduce a nonlocal discrete regularization framework on weighted graphs of the
arbitrary topologies for image and manifold processing. The approach considers the …

When performing visualization and classification, people often confront the problem of
dimensionality reduction. Isomap is one of the most promising nonlinear dimensionality …

This work presents a simple sequential growing and pruning algorithm for radial basis
function (RBF) networks. The algorithm referred to as growing and pruning (GAP)-RBF uses …

The increased use of digital tools such as smart phones, Internet of Things devices,
cameras, and microphones, has led to the produuction of big data. Large data …

Objective Medical data sets are usually small and have very high dimensionality. Too many
attributes will make the analysis less efficient and will not necessarily increase accuracy …