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Coherence resonance in neural networks: Theory and experiments
The paper is devoted to the review of the coherence resonance phenomenon in excitable
neural networks. In particular, we explain how coherence can be measured and how noise …
neural networks. In particular, we explain how coherence can be measured and how noise …
Dynamical principles in neuroscience
Dynamical modeling of neural systems and brain functions has a history of success over the
last half century. This includes, for example, the explanation and prediction of some features …
last half century. This includes, for example, the explanation and prediction of some features …
Memristive Rulkov neuron model with magnetic induction effects
The magnetic induction effects have been emulated by various continuous memristive
models but they have not been successfully described by a discrete memristive model yet …
models but they have not been successfully described by a discrete memristive model yet …
A discrete Chialvo–Rulkov neuron network coupled with a novel memristor model: Design, Dynamical analysis, DSP implementation and its application
In this paper, a novel discrete flux-controlled memristor model combining square and cosine
function is proposed and its properties are analyzed. Then, the discrete memristor is used to …
function is proposed and its properties are analyzed. Then, the discrete memristor is used to …
Offset boosting-entangled complex dynamics in the memristive rulkov neuron
A discrete memristor is introduced into the Rulkov neuron to mimic biological neuronal
synapse and modify firing dynamics. In the memristive Rulkov neuron, chaotic firing with …
synapse and modify firing dynamics. In the memristive Rulkov neuron, chaotic firing with …
[KSIĄŻKA][B] Synchronization: from coupled systems to complex networks
A modern introduction to synchronization phenomena, this text presents recent discoveries
and the current state of research in the field, from low-dimensional systems to complex …
and the current state of research in the field, from low-dimensional systems to complex …
Dynamics analysis and FPGA implementation of discrete memristive cellular neural network with heterogeneous activation functions
C Wang, D Luo, Q Deng, G Yang - Chaos, Solitons & Fractals, 2024 - Elsevier
The activation function, as an important component of artificial neural networks, endows
neural networks with rich dynamical phenomena by virtue of its nonlinear properties …
neural networks with rich dynamical phenomena by virtue of its nonlinear properties …
Synchronization transitions in a discrete memristor-coupled bi-neuron model
When synaptic connection is created to couple two neurons, the electromagnetic induction
current is unavoidably induced, which can be imitated by a flux-controlled memristor. To …
current is unavoidably induced, which can be imitated by a flux-controlled memristor. To …
Memristive effects on an improved discrete Rulkov neuron model
A change in neuronal-action potential can generate a magnetically induced current during
the release and propagation of intracellular ions. To better characterize the electromagnetic …
the release and propagation of intracellular ions. To better characterize the electromagnetic …
[HTML][HTML] Synchronization patterns in a network of diffusively delay-coupled memristive Chialvo neuron map
The inescapable presence of time delay in numerous real-world systems, particularly in
neuronal networks, prompts an exploration of its impact on synchronization dynamics. This …
neuronal networks, prompts an exploration of its impact on synchronization dynamics. This …