Abstract

Controlling and mastering the optical constant of thin film is a key factor concern for the optical coating. Each optical constant must be controlled very well to make the films meet requires desired. At present, there are many methods to characterize the optical constants of the films, for example: the envelop method, ellipsometry measurement, waveguide prism methode etc.[1]. All of them use numerical inversion technique to obtain the optical constants from the physical parameters measured. These methods are very well for treating their problems, but they have their main shortages of indefinite and very complex. We propose now an artifical neural network (ANN) model to simulate the relationship between the spectral character and optical constant of the thin films. ANN is a simplified mathematical model of biological network, it is extremely strong in dealing fuzzy and indefinite problem, and is widely used for the signal process and recgonization. Neural networks have the ability to learn directly from example data rather than following programmed rules based on a knowledge base, and can treat the problem extremely fast and tolerate data containg experimental error[2].

© 1995 Optical Society of America