The study of dynamics on artificial neurons and neuronal networks is of great significance to
understand brain functions and develop neuromorphic systems. Recently, memristive …

This work aims to provide a broad overview of computational techniques belonging to the
area of artificial intelligence tailored for identification of nonlinear dynamical systems. Both …

The nervous system is made of a large number of neurons. Time-varying balance between
excitatory and inhibitory neurons is important to activate appropriate modes of electrical …

This article introduces a novel model of asymmetric neural networks combined with
fractional difference memristors, which has both theoretical and practical implications in the …

On the basis of Hindmarsh-Rose neuron model, dynamical robustness and the transition of
firing modes of multilayer memristive neural network consisting of nonidentical neurons …

This paper studies the robust stability analysis for a class of memristive-based neural
networks (NN). The NN consists of a fractional order neutral type quaternion-valued leaky …

Nowadays, memory elements (memristor, memcapacitor, and meminductor) found a wider
range of applications in various fields like analog computation, memory-based circuits …

Due to complex frequency-driven and amplitude-driven nonlinear characteristics, various
memristor emulators have been used for design of hyperchaotic oscillators and their security …

At present, in the new hardware design work of deep learning, memristor as a non-volatile
memory with computing power has become a research hotspot. The weights in the deep …

In this paper, X-controlled universal fractional-order memelements (FOMEs) emulator is
proposed. The emulation circuit is realized using second-generation current conveyor (CCII) …