9 research outputs found

    The asymptotic iteration method for the angular spheroidal eigenvalues with arbitrary complex size parameter c

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    The asymptotic iteration method is applied, to calculate the angular spheroidal eigenvalues λℓm(c)\lambda^{m}_{\ell}(c) with arbitrary complex size parameter cc. It is shown that, the obtained numerical results of λℓm(c)\lambda^{m}_{\ell}(c) are all in excellent agreement with the available published data over the full range of parameter values ℓ\ell, mm, and cc. Some representative values of λℓm(c)\lambda^{m}_{\ell}(c) for large real cc are also given.Comment: 15 pages, 1 figur

    Identification of metallic objects using spectral MPT signatures: object characterisation and invariants

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    The early detection of terrorist threat objects, such as guns and knives, through improved metal detection, has the potential to reduce the number of attacks and improve public safety and security. To achieve this, there is considerable potential to use the felds applied and measured by a metal detector to discriminate between different shapes and different metals since, hidden within the field perturbation, is object characterisation information. The magnetic polarizability tensor (MPT) offers an economical characterisation of metallic objects that can be computed for different threat and non-threat objects and has an established theoretical background, which shows that the induced voltage is a function of the hidden object's MPT coeffcients. In this paper, we describe the additional characterisation information that measurements of the induced voltage over a range of frequencies offer compared to measurements at a single frequency. We call such object characterisations its MPT spectral signature. Then, we present a series of alternative rotational invariants for the purpose of classifying hidden objects using MPT spectral signatures. Finally, we include examples of computed MPT spectral signature characterisations of realistic threat and non-threat objects that can be used to train machine learning algorithms for classification purposes
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