55 resultados para Shaker architecture--Maine--Alfred--Maps.

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Synchronous chaos is investigated in the coupled system of two Logistic maps. Although the diffusive coupling admits all synchronized motions, the stabilities of their configurations are dependent on the transverse Lyapunov exponents while independent of the longitudinal Lyapunov exponents. It is shown that synchronous chaos is structurally stable with respect to the system parameters. The mean motion is the pseudo-orbit of an individual local map so that its dynamics can be described by the local map. (C) 2004 Elsevier Ltd. All rights reserved.

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Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on categorical data is still a challenge for SOM. This paper aims to extend standard SOM to handle feature values of categorical type. A batch SOM algorithm (NCSOM) is presented concerning the dissimilarity measure and update method of map evolution for both numeric and categorical features simultaneously.

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Carbon nanotubes have unprecedented mechanical properties as defect-free nanoscale building blocks, but their potential has not been fully realized in composite materials due to weakness at the interfaces. Here we demonstrate that through load-transfer-favored three-dimensional architecture and molecular level couplings with polymer chains, true potential of CNTs can be realized in composites as Initially envisioned. Composite fibers with reticulate nanotube architectures show order of magnitude improvement in strength compared to randomly dispersed short CNT reinforced composites reported before. The molecular level couplings between nanotubes and polymer chains results in drastic differences in the properties of thermoset and thermoplastic composite fibers, which indicate that conventional macroscopic composite theory falls to explain the overall hybrid behavior at nanoscale.

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A visual pattern recognition network and its training algorithm are proposed. The network constructed of a one-layer morphology network and a two-layer modified Hamming net. This visual network can implement invariant pattern recognition with respect to image translation and size projection. After supervised learning takes place, the visual network extracts image features and classifies patterns much the same as living beings do. Moreover we set up its optoelectronic architecture for real-time pattern recognition. (C) 1996 Optical Society of America

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To better understand the evolution of genome organization of eutherian mammals, comparative maps based on chromosome painting have been constructed between human and representative species of three eutherian orders: Xenarthra, Pholidota, and Eulipotyphla,