This study presents a cellular-based mapping for a special class of dynamical systems for embedding neuron models, by exploiting an efficient memristor crossbar-based circuit for its implementation. The resultant reconfigurable memristive dynamical circuit exhibits various bifurcation phenomena, and responses that are characteristic of dynamical systems. High programmability of the circuit enables it to be applied to real-time applications, learning systems, and analytically indescribable dynamical systems. Moreover, its efficient implementation platform makes it an appropriate choice for on-chip applications and prostheses. We apply this method to the Izhikevich, and FitzHugh–Nagumo neuron models as case studies, and investigate the dynami...
The paper considers a class of CNNs, named dynamic-memristor (DM) CNNs, where each cell has an ideal...
This manuscript provides a comprehensive tutorial on the operating principles of a bio-inspired Cell...
The design of Memristor Oscillatory Neurocomputers for pattern recognition tasks may not leave aside...
This study presents a cellular-based mapping for a special class of dynamical systems for embed-ding...
This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromor...
This paper deals with the problem of modelling the classical dynamics of cortical neurons by using m...
The paper introduces a class of memristor neural networks (NNs) that are characterized by the follow...
The memristor is a device whose resistance changes depending on the polarity and magnitude of a volt...
In this paper, we report a novel memristor-based cellular neural network (CNN) without equilibrium p...
International audienceBesides being at the core of novel ultra-high density low-power non-volatile m...
Information processing in the brain takes place in a dense network of neurons connected through syna...
Abstract Nowadays, processing of data via neuromorphic non‐linear dynamics is a key element for brai...
A cellular neural network (CNN) is a massively parallel analog array processor capable of solving va...
Chaotic neural networks are able to reproduce chaotic dynamics observable in the brain of various li...
SummaryA cellular neural network (CNN) is a massively parallel analog array processor capable of sol...
The paper considers a class of CNNs, named dynamic-memristor (DM) CNNs, where each cell has an ideal...
This manuscript provides a comprehensive tutorial on the operating principles of a bio-inspired Cell...
The design of Memristor Oscillatory Neurocomputers for pattern recognition tasks may not leave aside...
This study presents a cellular-based mapping for a special class of dynamical systems for embed-ding...
This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromor...
This paper deals with the problem of modelling the classical dynamics of cortical neurons by using m...
The paper introduces a class of memristor neural networks (NNs) that are characterized by the follow...
The memristor is a device whose resistance changes depending on the polarity and magnitude of a volt...
In this paper, we report a novel memristor-based cellular neural network (CNN) without equilibrium p...
International audienceBesides being at the core of novel ultra-high density low-power non-volatile m...
Information processing in the brain takes place in a dense network of neurons connected through syna...
Abstract Nowadays, processing of data via neuromorphic non‐linear dynamics is a key element for brai...
A cellular neural network (CNN) is a massively parallel analog array processor capable of solving va...
Chaotic neural networks are able to reproduce chaotic dynamics observable in the brain of various li...
SummaryA cellular neural network (CNN) is a massively parallel analog array processor capable of sol...
The paper considers a class of CNNs, named dynamic-memristor (DM) CNNs, where each cell has an ideal...
This manuscript provides a comprehensive tutorial on the operating principles of a bio-inspired Cell...
The design of Memristor Oscillatory Neurocomputers for pattern recognition tasks may not leave aside...