Noise assisted image processing by ensembles of R-SETs

Abstract

We study how noise can assist the processing of an image in a resistance-single electron transistor (R-SET) model. The image is an 8-bit black and white picture. Every grey level is codified linearly into a sub-threshold input potential applied for a prescribed time window to an ensemble of R-SETs that transforms it into a spiking frequency. The addition of a background white noise potential of high amplitude permits the ensemble to process the image by means of the stochastic resonance phenomenon. Aside from the positive aspects, we analyse the negative impact of using noise and how we can minimize it using redundancy and a longer measuring time. The results are compared with the case of the addition of a constant potential to the codified potential to scale it up to the supra-threshold regime.

Graphical abstract

A background white noise potential of high amplitude permits an ensemble of R-SET units to process an image by means of the stochastic resonance phenomenon. The negative impacts can be minimized using redundancy and a longer measuring time.

Keywords:

• Resistance-single electron transistor (R-SET)
• image processing
• noise assisted detection
• stochastic resonance
• redundancy

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Ministerio de Economía y Competitividad [project number MAT2015-65011-P] and the Generalitat Valenciana [project number Prometeo/GV/0069].