A Neuron Based Switch: Application to Low Power Mixed Signal Circuits

TL;DR

This paper presents a VLSI implementation of a biologically inspired neuron model to create a low power mixed-signal circuit, demonstrating how cortical neuron firing patterns can optimize power consumption in practical applications.

Contribution

It introduces a neuron-based switch using the Izhikevich model for low power mixed-signal circuit design, bridging neuroscience and hardware engineering.

Findings

Significant power reduction in the differential amplifier.

Successful implementation of spike and burst firing patterns in hardware.

Demonstrated applicability of cortical neuron models in practical circuits.

Abstract

Human brain is functionally and physically complex. This 'complexity' can be seen as a result of biological design process involving extensive use of concepts such as modularity and hierarchy. Over the past decade, deeper insights into the functioning of cortical neurons have led to the development of models that can be implemented in hardware. The implementation of biologically inspired spiking neuron networks in silicon can provide solutions to difficult cognitive tasks. The work reported in this paper is an application of a VLSI cortical neuron model for low power design. The VLSI implementation shown in this paper is based on the spike and burst firing pattern of cortex and follows the Izhikevich neuron model. This model is applied to a DC differential amplifier as practical application of power reduction