A novel FOCAL technique based on BP-ANN

In this paper, the feed-forward back-propagation artificial neural network (BP-ANN) algorithm is introduced in the traditional Focus Calibration using Alignment procedure (FOCAL) technique, and a novel FOCAL technique based on BP-ANN is proposed. The effects of the parameters, such as the number of neurons on the hidden-layer and the number of training epochs, on the measurement accuracy are analyzed in detail. It is proved that the novel FOCAL technique based on BP-ANN is more reliable and it is a better choice for measurement of the image quality parameters. (c) 2005 Elsevier GmbH. All rights reserved.

Surface relief resonant Brewster niters with multiple channels

In this paper, a new type of resonant Brewster filters (RBF) with surface relief structure for the multiple channels is first presented by using the rigorous coupled-wave analysis and the S-matrix method. By tuning the depth of homogeneous layer which is under the surface relief structure, the multiple channels phenomenon is obtained. Long range, extremely low sidebands and multiple channels are found when the RBF with surface relief structure is illuminated with Transverse Magnetic incident polarization light near the Brewster angle calculated with the effective media theory of sub wavelength grating. Moreover, the wavelengths of RBF with surface relief structure can be easily shifted by changing the depth of homogeneous layer while its optical properties such as low sideband reflection and narrow band are not spoiled when the depth is changed. Furthermore, the variation of the grating thickness does not effectively change the resonant wavelength of RBF, but have a remarkable effect on its line width, which is very useful for designing such filters with different line widths at desired wavelength.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.