Logo image
Use of artificial neural networks on optical track width measurements
Journal article   Peer reviewed

Use of artificial neural networks on optical track width measurements

Richard J Smith, Chung W See, Mike G Somekh and Andrew Yacoot
Applied optics (2004), Vol.46(22), pp.4857-4866
08/01/2007
DOI: 10.1364/AO.46.004857
PMID: 17676087

View Online

Abstract

We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60 nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.

Details

Metrics

Logo image