138 resultados para volume optimisation


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Plane wave scattering from a flat surface consisting of two periodic arrays of ring elements printed on a grounded dielectric sheet is investigated. It is shown that the reflection phase variation as a function of ring diameter is controlled by the difference in the centre resonant frequency of the two arrays. Simulated and measured results at X-band demonstrate that this parameter can be used to reduce the gradient and improve the linearity of the reflection phase versus ring size slope. These are necessary conditions for the re-radiating elements to maximise the bandwidth of a microstrip reflectarray antenna. The scattering properties of a conventional dual resonant multilayer structure and an array of concentric rings printed on a metal backed dielectric substrate are compared and the trade-off in performance is discussed.

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This paper, chosen as a best paper from the 2005 SAMOS Workshop on Computer Systems: describes the for the first time the major Abhainn project for automated system level design of embedded signal processing systems. In particular, this describes four key novelties: novel algorithm modelling techniques for DSP systems, automated implementation realisation, algorithm transformation for system optimisation and automated inter-processor communication. This is applied to two complex systems: a radar and sonar system. In both cases technology which allows non-experts to automatically create low-overhead, high performance embedded signal processing systems is exhibited.

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Novel technology dependent scaling parameters i.e. spacer to gradient ratio and effective channel length (Leff) are proposed for source/drain engineered DG MOSFET, and their significance in minimizing short channel effects (SCES) in high-k gate dielectrics is discussed in detail. Results show that a high-k dielectric should be associated with a higher spacer to gradient ratio to minimise SCEs The analytical model agrees with simulated data over the entire range of spacer widths, doping gradients, high-k gate dielectrics and effective channel lengths.

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A new search-space-updating technique for genetic algorithms is proposed for continuous optimisation problems. Other than gradually reducing the search space during the evolution process with a fixed reduction rate set ‘a priori’, the upper and the lower boundaries for each variable in the objective function are dynamically adjusted based on its distribution statistics. To test the effectiveness, the technique is applied to a number of benchmark optimisation problems in comparison with three other techniques, namely the genetic algorithms with parameter space size adjustment (GAPSSA) technique [A.B. Djurišic, Elite genetic algorithms with adaptive mutations for solving continuous optimization problems – application to modeling of the optical constants of solids, Optics Communications 151 (1998) 147–159], successive zooming genetic algorithm (SZGA) [Y. Kwon, S. Kwon, S. Jin, J. Kim, Convergence enhanced genetic algorithm with successive zooming method for solving continuous optimization problems, Computers and Structures 81 (2003) 1715–1725] and a simple GA. The tests show that for well-posed problems, existing search space updating techniques perform well in terms of convergence speed and solution precision however, for some ill-posed problems these techniques are statistically inferior to a simple GA. All the tests show that the proposed new search space update technique is statistically superior to its counterparts.