Proposal for a Leaky-Integrate-Fire Spiking Neuron based on Magneto-Electric Switching of Ferro-magnets

09/29/2016
by   Akhilesh Jaiswal, et al.
0

The efficiency of the human brain in performing classification tasks has attracted considerable research interest in brain-inspired neuromorphic computing. Hardware implementations of a neuromorphic system aims to mimic the computations in the brain through interconnection of neurons and synaptic weights. A leaky-integrate-fire (LIF) spiking model is widely used to emulate the dynamics of neuronal action potentials. In this work, we propose a spin based LIF spiking neuron using the magneto-electric (ME) switching of ferro-magnets. The voltage across the ME oxide exhibits a typical leaky-integrate behavior, which in turn switches an underlying ferro-magnet. Due to the effect of thermal noise, the ferro-magnet exhibits probabilistic switching dynamics, which is reminiscent of the stochasticity exhibited by biological neurons. The energy-efficiency of the ME switching mechanism coupled with the intrinsic non-volatility of ferro-magnets result in lower energy consumption, when compared to a CMOS LIF neuron. A device to system-level simulation framework has been developed to investigate the feasibility of the proposed LIF neuron for a hand-written digit recognition problem

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/02/2015

A CMOS Spiking Neuron for Dense Memristor-Synapse Connectivity for Brain-Inspired Computing

Neuromorphic systems that densely integrate CMOS spiking neurons and nan...
research
05/19/2017

Voltage-Driven Domain-Wall Motion based Neuro-Synaptic Devices for Dynamic On-line Learning

Conventional von-Neumann computing models have achieved remarkable feats...
research
10/06/2012

Reply to Comments on Neuroelectrodynamics: Where are the Real Conceptual Pitfalls?

The fundamental, powerful process of computation in the brain has been w...
research
06/29/2019

A Power Efficient Artificial Neuron Using Superconducting Nanowires

With the rising societal demand for more information-processing capacity...
research
08/16/2017

Stochastic IMT (insulator-metal-transition) neurons: An interplay of thermal and threshold noise at bifurcation

A stochastic neuron, a key hardware kernel for implementing stochastic n...
research
11/02/2015

Spiking Analog VLSI Neuron Assemblies as Constraint Satisfaction Problem Solvers

Solving constraint satisfaction problems (CSPs) is a notoriously expensi...
research
07/29/2020

A superconducting nanowire spiking element for neural networks

As the limits of traditional von Neumann computing come into view, the b...

Please sign up or login with your details

Forgot password? Click here to reset