53 research outputs found
Neural Distributed Autoassociative Memories: A Survey
Introduction. Neural network models of autoassociative, distributed memory
allow storage and retrieval of many items (vectors) where the number of stored
items can exceed the vector dimension (the number of neurons in the network).
This opens the possibility of a sublinear time search (in the number of stored
items) for approximate nearest neighbors among vectors of high dimension. The
purpose of this paper is to review models of autoassociative, distributed
memory that can be naturally implemented by neural networks (mainly with local
learning rules and iterative dynamics based on information locally available to
neurons). Scope. The survey is focused mainly on the networks of Hopfield,
Willshaw and Potts, that have connections between pairs of neurons and operate
on sparse binary vectors. We discuss not only autoassociative memory, but also
the generalization properties of these networks. We also consider neural
networks with higher-order connections and networks with a bipartite graph
structure for non-binary data with linear constraints. Conclusions. In
conclusion we discuss the relations to similarity search, advantages and
drawbacks of these techniques, and topics for further research. An interesting
and still not completely resolved question is whether neural autoassociative
memories can search for approximate nearest neighbors faster than other index
structures for similarity search, in particular for the case of very high
dimensional vectors.Comment: 31 page
Idiom treatment experiments in machine translation
Idiomatic expressions pose a particular challenge for the today\u27;s Machine Translation systems, because their translation mostly does not result literally, but logically. The present dissertation shows, how with the help of a corpus, and morphosyntactic rules, such idiomatic expressions can be recognized and finally correctly translated. The work leads the reader in the first chapter generally to the field of Machine Translation and following that, it focuses on the special field of Example-based Machine Translation. Next, an important part of the doctoral thesis dissertation is devoted to the theory of idiomatic expressions. The practical part of the thesis describes how the hybrid Example-based Machine Translation system METIS-II, with the help of morphosyntactic rules, is able to correctly process certain idiomatic expressions and finally, to translate them. The following chapter deals with the function of the transfer system CAT2 and its handling of the idiomatic expressions. The last part of the thesis includes the evaluation of three commercial systems, namely SYSTRAN, T1 Langenscheidt, and Power Translator Pro, with respect to continuous and discontinuous idiomatic expressions. For this, both small corpora and a part of the extensive corpus Europarl and the Digital Lexicon of the German Language in 20th century were processed, firstly manually and then automatically. The dissertation concludes with results from this evaluation.Idiomatische Redewendungen stellen für heutige maschinelle Übersetzungssysteme eine besondere Herausforderung dar, da ihre Übersetzung nicht wörtlich, sondern stets sinngemäß erfolgen muss. Die vorliegende Dissertation zeigt, wie mit Hilfe eines Korpus sowie morphosyntaktischer Regeln solche idiomatische Redewendungen erkannt und am Ende richtig übersetzt werden können. Die Arbeit führt den Leser im ersten Kapitel allgemein in das Gebiet der Maschinellen Übersetzung ein und vertieft im Anschluss daran das Spezialgebiet der Beispielbasierten Maschinellen Übersetzung. Im Folgenden widmet sich ein wesentlicher Teil der Doktorarbeit der Theorie über idiomatische Redewendungen. Der praktische Teil der Arbeit beschreibt wie das hybride Beispielbasierte Maschinelle Übersetzungssystem METIS-II mit Hilfe von morphosyntaktischen Regeln befähigt wurde, bestimmte idiomatische Redewendungen korrekt zu bearbeiten und am Ende zu übersetzen. Das nachfolgende Kapitel behandelt die Funktion des Transfersystems CAT2 und dessen Umgang mit idiomatischen Wendungen. Der letzte Teil der Arbeit beinhaltet die Evaluation von drei kommerzielle Systemen, nämlich SYSTRAN, T1 Langenscheidt und Power Translator Pro, in Bezug auf deren Umgang mit kontinuierlichen und diskontinuierlichen idiomatischen Redewendungen. Hierzu wurden sowohl kleine Korpora als auch ein Teil des umfangreichen Korpus Europarl und des Digatalen Wörterbuchs der deutschen Sprache des 20. Jh. erst manuell und dann maschinell bearbeitet. Die Dissertation wird mit Folgerungen aus der Evaluation abgeschlossen
Architectural Support for Efficient Communication in Future Microprocessors
Traditionally, the microprocessor design has focused on the computational aspects
of the problem at hand. However, as the number of components on a single chip
continues to increase, the design of communication architecture has become a crucial
and dominating factor in defining performance models of the overall system. On-chip
networks, also known as Networks-on-Chip (NoC), emerged recently as a promising
architecture to coordinate chip-wide communication.
Although there are numerous interconnection network studies in an inter-chip
environment, an intra-chip network design poses a number of substantial challenges
to this well-established interconnection network field. This research investigates designs
and applications of on-chip interconnection network in next-generation microprocessors
for optimizing performance, power consumption, and area cost. First,
we present domain-specific NoC designs targeted to large-scale and wire-delay dominated
L2 cache systems. The domain-specifically designed interconnect shows 38%
performance improvement and uses only 12% of the mesh-based interconnect. Then,
we present a methodology of communication characterization in parallel programs
and application of characterization results to long-channel reconfiguration. Reconfigured
long channels suited to communication patterns enhance the latency of the
mesh network by 16% and 14% in 16-core and 64-core systems, respectively. Finally,
we discuss an adaptive data compression technique that builds a network-wide frequent value pattern map and reduces the packet size. In two examined multi-core
systems, cache traffic has 69% compressibility and shows high value sharing among
flows. Compression-enabled NoC improves the latency by up to 63% and saves energy
consumption by up to 12%
NASA Space Engineering Research Center Symposium on VLSI Design
The NASA Space Engineering Research Center (SERC) is proud to offer, at its second symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories and the electronics industry. These featured speakers share insights into next generation advances that will serve as a basis for future VLSI design. Questions of reliability in the space environment along with new directions in CAD and design are addressed by the featured speakers
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