The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired …

Neuro-fuzzy systems is a soft computing technique for develo** intelligent systems that
solve complex real-world problems in a way that closely resembles human reasoning. In this …

This paper is concerned with the finite-time synchronization problem of drive-response
inertial memristive neural networks with time delay. First, by choosing suitable variable …

Recent work has considered a class of cellular neural networks (CNNs) where each cell
contains an ideal capacitor and an ideal flux-controlled memristor. One main feature is that …

Recent papers in the literature introduced a class of neural networks (NNs) with memristors,
named dynamic-memristor (DM) NNs, such that the analog processing takes place in the …

In this paper, the motion dynamics of a large tanker is modeled by the generalized
ellipsoidal function-based fuzzy neural network (GEBF-FNN). The reference model of tanker …

Modern computing architecture based on the separation of memory and processing leads to
a well known problem called the von Neumann bottleneck, a restrictive limit on the data …

In this paper, we introduce a memristor-crossbar based hardware in order to implement the
Clustering Fuzzification Algorithm with on-chip learning capability. The proposed Clustering …

Memristor is a newly invented device and since it has been found, has drawn a lot of
attention from integrated electronics designers because of its nanometer size and special …

Active learning method (ALM) is a powerful fuzzy-based soft computing methodology
suitable for various applications such as function modeling, control systems, clustering and …