A simple CMOS circuitry using very less number of MOSFETs reproduce most of the electrophysiological cortical neuron types and is capable of producing a variety of different behaviors with diversity similar to that of real biological neuron cell. The firing pattern of basic cell classes like regular spiking (RS), chattering (CH), intrinsic bursting (IB) and fast spiking(FS) are obtained with a simple adjustment of only one biasing voltage makes circuit suitable for applications in reconfigurable neuromorphic devices that implement biologically resemble circuit of cortex. This paper discusses spice simulation of the various spiking pattern ability with required and firing frequency of a given cell type. The circuit operation is verified for ...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Continuous improvements in the VLSI domain have enabled the technology to mimic the neuro biological...
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Prese...
Abstract — This paper presents a novel analogue VLSI circuitry that reproduces spiking and bursting ...
Abstract — This paper presents an analogue integrated circuit implementation of a cortical neuron mo...
Nowadays, many software solutions are currently available for simulating neuron models. Less convent...
Abstract — This paper presents an analogue VLSI circuit intended to be used in a neural network arch...
We have used analog VLSI technology to model a class of biological neural circuits known as central ...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
Brain-inspired chips are being designed to efficiently process complex information and accomplish ta...
Cortical circuits in the brain have long been recognised for their information processing capabiliti...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
Cortical circuits in the brain have long been recognised for their information processing capabiliti...
International audienceA VLSI implementation of a Silicon-Controlled Rectifier (SCR)-based Neuron tha...
Abstract—Hardware implementations of spiking neural net-works offer promising solutions for a wide s...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Continuous improvements in the VLSI domain have enabled the technology to mimic the neuro biological...
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Prese...
Abstract — This paper presents a novel analogue VLSI circuitry that reproduces spiking and bursting ...
Abstract — This paper presents an analogue integrated circuit implementation of a cortical neuron mo...
Nowadays, many software solutions are currently available for simulating neuron models. Less convent...
Abstract — This paper presents an analogue VLSI circuit intended to be used in a neural network arch...
We have used analog VLSI technology to model a class of biological neural circuits known as central ...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
Brain-inspired chips are being designed to efficiently process complex information and accomplish ta...
Cortical circuits in the brain have long been recognised for their information processing capabiliti...
Hardware implementations of spiking neurons can be extremely useful for a large variety of applicati...
Cortical circuits in the brain have long been recognised for their information processing capabiliti...
International audienceA VLSI implementation of a Silicon-Controlled Rectifier (SCR)-based Neuron tha...
Abstract—Hardware implementations of spiking neural net-works offer promising solutions for a wide s...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Continuous improvements in the VLSI domain have enabled the technology to mimic the neuro biological...
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Prese...