By Gary Frazier (auth.), Stuart K. Tewksbury, Bradley W. Dickinson, Stuart C. Schwartz (eds.)
The 1987 Princeton Workshop on set of rules, structure and expertise matters for types of Concurrent Computation was once equipped as an interdisciplinary paintings store emphasizing present examine instructions towards concurrent computing platforms. With members from a number of varied fields of specialization, the workshop cov ered a wide selection of issues, notwithstanding on no account an entire move portion of matters during this swiftly relocating box. The papers integrated during this ebook have been ready for the workshop and, taken jointly, supply a view of the huge variety of concerns and replacement instructions being explored. to prepare a few of the papers, the booklet has been divided into 5 components. half I considers new expertise instructions. half II emphasizes underlying theoretical matters. conversation matters, that are advert wearing nearly all of papers, are in particular highlighted partially III. half IV comprises papers stressing the fault tolerance and reliability of platforms. eventually, half V contains systems-oriented papers, the place the procedure levels from VLSI circuits via strong parallel desktops. a lot of the preliminary making plans of the workshop used to be accomplished via an off-the-cuff AT&T Bell Laboratories staff inclusive of Mehdi Hatamian, Vijay Kumar, Adri aan Ligtenberg, Sailesh Rao, P. Subrahmanyam and myself. we're thankful to Stuart Schwartz, either for the help of Princeton collage and for his orga nizing neighborhood preparations for the workshop, and to the contributors of the organizing committee, whose innovations for members and dialogue issues have been par ticularly invaluable. A. Rosenberg, and A. T.
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Additional info for Concurrent Computations: Algorithms, Architecture, and Technology
The answer to this questions depends a large part on the application involved. The more communications intensive a problem is the better it will be for optics. The most likely candidates will be switching computers, super computers, and specialized signal processors. Some of the quoted strengths of electronics are a bit misleading. The powers and speeds of optical and electronic gates are constantly being compared. This is not a fair comparison since communication costs are not really factored in.
Carpenter and S. Grossberg, ART 2: Self-Organization of Stable Category Recognition Code for Analog Input Patterns, Applied Optics, 26, p. 4919, (1987). P Lippmann, An Introduction to Computing with Neural Nets, IEEE ASSP Magazine, 4/2, p. 4, (1987). S. Denker, D. Schwartz, B. Wittner, S. Solla, R. Jackel and J. Hopfield, Large Automatic Learning, Rule Extraction, and Generalization, Complex Systems, 1, p. 877, (1987). D. E. P. Graf, B. S. Denker, Artificial Neural Networks for Computing, J. Vac.
A vector is given at the input of the network and is compared with all the stored features in parallel. 4. 3: A network set up for pattern classification or feature extraction. The '+' and the '-' mark excitatory and inhibitory connections respectively (an excitatory connection inputs current into the line; an inhibitory connection draws current from the line). Below the schematic the stored vectors are indicated. unit connected to that feature goes high indicating the presence of the feature in the input.