International audienceA VLSI implementation of a Silicon-Controlled Rectifier (SCR)-based Neuron that has the functionality of the leaky-integrate and fire model (LIF) of spiking neurons is introduced. The silicon-controlled rectifier is not straightforward to efficiently migrate to VLSI. Therefore, we propose a MOS transistor-based circuit that provides the same functionality as the SCR. The results of this work are based on Spice simulation using open libraries and on VLSI layout and post layout simulations for a 65 nm CMOS processView the article online for updates and enhancements. You may also like Characterization of dynamics and information processing of integrate-andfire neuron models JunHyuk Woo, Soon Ho Kim, Kyungreem Han et al
International audienceWe demonstrate a variety of biologically relevant dynamical behaviors building...
An increasing number of research groups are developing custom hybrid analog/digital very large scale...
A simple CMOS circuitry using very less number of MOSFETs reproduce most of the electrophysiological...
International audienceA VLSI implementation of a Silicon-Controlled Rectifier (SCR)-based Neuron tha...
This final year project is about the VLSI implementation of a neuron. It introduces the development ...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
In this paper we present the design, implementation and preliminary results from a silicon neuron (S...
Spiking Neural Networks propose to mimic nature’s way of recognizing patterns and making decisions i...
International audienceWe introduce an ultra-compact electronic circuit that realizes the leaky-integ...
Abstract. We describe an improved spiking silicon neuron (SN) [6] that approximates the dynamics of ...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Abstract — This paper presents a novel analogue VLSI circuitry that reproduces spiking and bursting ...
We discuss the integration architecture of spiking neu-rons, predicted to be next-generation basic c...
We present an analogue Very Large Scale Integration (aVLSI) implementation that uses first-order log...
International audienceWe demonstrate a variety of biologically relevant dynamical behaviors building...
An increasing number of research groups are developing custom hybrid analog/digital very large scale...
A simple CMOS circuitry using very less number of MOSFETs reproduce most of the electrophysiological...
International audienceA VLSI implementation of a Silicon-Controlled Rectifier (SCR)-based Neuron tha...
This final year project is about the VLSI implementation of a neuron. It introduces the development ...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
In this paper we present the design, implementation and preliminary results from a silicon neuron (S...
Spiking Neural Networks propose to mimic nature’s way of recognizing patterns and making decisions i...
International audienceWe introduce an ultra-compact electronic circuit that realizes the leaky-integ...
Abstract. We describe an improved spiking silicon neuron (SN) [6] that approximates the dynamics of ...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Abstract — This paper presents a novel analogue VLSI circuitry that reproduces spiking and bursting ...
We discuss the integration architecture of spiking neu-rons, predicted to be next-generation basic c...
We present an analogue Very Large Scale Integration (aVLSI) implementation that uses first-order log...
International audienceWe demonstrate a variety of biologically relevant dynamical behaviors building...
An increasing number of research groups are developing custom hybrid analog/digital very large scale...
A simple CMOS circuitry using very less number of MOSFETs reproduce most of the electrophysiological...