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Online ISSN 1350-911X Print ISSN 0013-5194

Electronics Letters

Volume 48, Issue 22, 25 October 2012

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Volume 48, Issue 22

25 October 2012

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In Brief

  • Features

    • Interview
      Shaking it up
      • Author(s): J. Baldwin
      • Source: Electronics Letters, Volume 48, Issue 22, page: 1375 –1375
      • DOI:  10.1049/el.2012.3595
      • Type: Article
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      • p. 1375 (1)
        Researchers at the University of Notre Dame in the US have developed an Er/Yb co-doped compound semiconductor native oxide that significantly enhances laser absorption efficiency, thus increasing the viability of realising a low-cost, monolithically-integrated wavelength amplifier with on-board pump laser source.Wavelength division multiplexing is a widely used technology in long haul optical communications networks where as many as 100 different closely spaced channels of data are simultaneously transmitted in an optical fibre, with each channel sent by a slightly different wavelength laser. Fibre amplifiers are used to amplify all of these signals simultaneously within the fibre all optically, so that optical-electrical-optical conversions requiring a number of components are unnecessary. A pump laser excites doping atoms which can then provide gain (optical amplification) for the signals traveling in the fibre, boosting their power as much as 1000 times. These signals are photons generated by single wavelength lasers, all spaced 50-100 GHz apart at wavelengths around ∼1550 nm.
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      Inside View

  • Electromagnetism

    • Evaluation of eigenmode quality factor of large complex cavities based on PEC linear finite element formulation
      • Author(s): C.L. Zekios ; P.C. Allilomes ; G.A. Kyriacou
      • Source: Electronics Letters, Volume 48, Issue 22, p. 1399 –1401
      • DOI:  10.1049/el.2012.1852
      • Type: Article
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      • p. 1399 –1401 (3)
        Finite conductivity losses of arbitrarily shaped and inhomogeneously loaded two- and three-dimensional structures are evaluated to a practical accuracy, solving a linear eigenproblem formulated on perfect electric conductors (PECs). This scheme mimics the analytical approach classically employed for canonically shaped waveguides and cavities. The normal electric and tangential magnetic modal fields, obtained assuming all metallic surfaces as PECs, are practically unchanged in the finite conductivity case. These are utilised to evaluate the previously vanished tangential electric and normal magnetic field components through the Leontovich impedance conditions and in turn the related attenuation factors for 2D and quality factors for 3D structures. Validation against commercial electromagnetic simulators and nonlinear FEM formulations incorporating Leontovich conditions yields an agreement better than 2%.
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  • Information and communications

    • Low-complexity iteration control algorithm for multi-rate partially parallel layered LDPC decoders
      • Author(s): Y.-H. Chien ; M.-K. Ku ; J.-B. Liu
      • Source: Electronics Letters, Volume 48, Issue 22, p. 1406 –1407
      • DOI:  10.1049/el.2012.2625
      • Type: Article
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      • p. 1406 –1407 (2)
        Concurrent partially parallel syndrome computation reduces complexity but incurs increased error rates due to the hard decision flipping (HDF) problem. Proposed is a low-complexity iteration control algorithm (LC-ICA) that eliminates BER degradation. The HDF rate is also used to terminate undecodable blocks to further save iterations. The algorithm works over multiple code rates. The implementation results show that a six-rate LC-ICA requires only 23.32% of a single-rate fully-parallel syndrome hardware.
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      Universum linear discriminant analysis
      • Author(s): X.H. Chen ; S.C. Chen ; H. Xue
      • Source: Electronics Letters, Volume 48, Issue 22, p. 1407 –1409
      • DOI:  10.1049/el.2012.2506
      • Type: Article
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      • p. 1407 –1409 (3)
        Universum learning has been used for classification and clustering, and obtains favourable improvements with the help of Universum – the samples that do not belong to either class of interest. In this reported work, universum learning is extended to dimensionality reduction by incorporating it with linear discriminant analysis (LDA). However, for the C-class problem, LDA can get at most C−1 projection directions due to the rank limitation. The C−1 directions are not enough for sufficient discrimination, which has motivated the adaption of the one-against-one trick to decompose the original C-class LDA into 0.5C(C−1) binary LDA ones for getting more directions. Uiniversum learning is then introduced to each binary LDA and the method is termed as universum linear discriminant analysis (ULDA). ULDA aims to find discriminant directions by maximising the distance between two target classes and simultaneously minimising the distance between the Universum and the mean of the target classes. The experiments on UCI datasets demonstrate the advantages and effectiveness of the ULDA.
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