28 resultados para James Bishop Jr.

em CentAUR: Central Archive University of Reading - UK


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The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been used for a variety of tasks, the most popular being real-time pattern recognition, and they can be implemented easily in hardware as they use standard random access memories. In operation, a series of images of an object are shown to the network, each being processed suitably and effectively stored in a memory called a discriminator. Then, when another image is shown to the system, it is processed in a similar manner and the system reports whether it recognises the image; is the image sufficiently similar to one already taught? If the system is to be able to recognise and discriminate between m-objects, then it must contain m-discriminators. This can require a great deal of memory. This paper describes various ways in which memory requirements can be reduced, including a novel method for multiple discriminator n-tuple networks used for pattern recognition. By using this method, the memory normally required to handle m-objects can be used to recognise and discriminate between 2^m — 2 objects.

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The cooled infrared filters and dichroic beam splitters manufactured for the Mid-Infrared Instrument are key optical components for the selection and isolation of wavelengths in the study of astrophysical properties of stars, galaxies, and other planetary objects. We describe the spectral design and manufacture of the precision cooled filter coatings for the spectrometer (7 K) and imager (9 K). Details of the design methods used to achieve the spectral requirements, selection of thin film materials, deposition technique, and testing are presented together with the optical layout of the instrument. (C) 2008 Optical Society of America.