Optical network for real-time face recognition

An optical network is described that is capable of recognizing at standard video rates the identity of faces for which it has been trained. The faces are presented under a wide variety of conditions to the system and the classification performance is measured. The system is trained by gradually adapting photorefractive holograms

Electrical fixing of photorefractive holograms in Sr0.75Ba0.25Nb2O6

Photorefractive holograms stored in Sr0.75Ba0.25Nb2O6 crystals are electrically fixed at room temperature. The fixed holograms can be read out directly or after a positive-voltage pulse is applied that can dramatically enhance the diffraction efficiency. Single gratings as well as images are recorded and fixed

Optical multilayer neural networks

In order to implement fully adaptive optical multilayer neural networks, a number of issues involving both learning algorithms and device technologies need to be addressed. In this paper, we present some important modifications to existing learning algorithms that serve to simplify optical architectures and allow the use of simple optical devices

Learning in large optical networks

In a holographic optical learning network, the decay of multiply exposed holographic interconnections can adversely affect the training of the network. A new dynamic photorefractive holographic memory is described that allows an arbitrarily long sequence of adaptations by rejuvenating decayed holograms with a simple all-optical feedback loop

A parametrized three-dimensional model for MEMS thermal shear-stress sensors

This paper presents an accurate and efficient model of MEMS thermal shear-stress sensors featuring a thin-film hotwire on a vacuum-isolated dielectric diaphragm. We consider three-dimensional (3-D) heat transfer in sensors operating in constant-temperature mode, and describe sensor response with a functional relationship between dimensionless forms of hotwire power and shear stress. This relationship is parametrized by the diaphragm aspect ratio and two additional dimensionless parameters that represent heat conduction in the hotwire and diaphragm. Closed-form correlations are obtained to represent this relationship, yielding a MEMS sensor model that is highly efficient while retaining the accuracy of three-dimensional heat transfer analysis. The model is compared with experimental data, and the agreement in the total and net hotwire power, the latter being a small second-order quantity induced by the applied shear stress, is respectively within 0.5% and 11% when uncertainties in sensor geometry and material properties are taken into account. The model is then used to elucidate thermal boundary layer characteristics for MEMS sensors, and in particular, quantitatively show that the relatively thick thermal boundary layer renders classical shear-stress sensor theory invalid for MEMS sensors operating in air. The model is also used to systematically study the effects of geometry and material properties on MEMS sensor behavior, yielding insights useful as practical design guidelines

Electric Character of Strange Stars

Using the Thomas-Fermi model, we investigated the electric characteristics of a static non-magnetized strange star without crust in this paper. The exact solutions of electron number density and electric field above the quark surface are obtained. These results are useful if we are concerned about physical processes near the quark matter surfaces of strange stars.Comment: 4 pages, 2 figures, LaTeX, Published in Chinese Physics Letters, Vol.16, p.77