5 resultados para Quasi-Likelihood
em Cochin University of Science
Resumo:
The question of stability of black hole was first studied by Regge and Wheeler who investigated linear perturbations of the exterior Schwarzschild spacetime. Further work on this problem led to the study of quasi-normal modes which is believed as a characteristic sound of black holes. Quasi-normal modes (QNMs) describe the damped oscillations under perturbations in the surrounding geometry of a black hole with frequencies and damping times of oscillations entirely fixed by the black hole parameters.In the present work we study the influence of cosmic string on the QNMs of various black hole background spacetimes which are perturbed by a massless Dirac field.
Resumo:
Large amplitude local density fluctuations in a thin superfluid He film is considered. It is shown that these large amplitude fluctuations travel and behave like "quasi-solitons" under collision, even when the full nonlinearity arising from the Van der Waals potential is taken into account.
Resumo:
A compact, planar, wideband antenna designed by modifying the coplanar waveguide is presented in this letter. The proposed antenna finds a wide range of applications including advanced wireless systems (AWS), DCS-1800, DCS-1900/PCS/PHS, WiBro, BlueTooth/WLAN/WiBree/ZigBee, DMB, Global Star Satellite Phones, and digital cordless phones. Wide bandwidth > 75% centered at 2.50 GHz, quasi-omnidirectional radiation coverage along with moderate gain and efficiency are the salient features of the antenna. A prototype fabricated on a substrate with dielectric constant 4.4 and thickness 1.6 mm occupies an area of (31times 64) mm2. Details of antenna design and discussions on the effect of various antenna parameters on the radiation characteristics are presented.
Resumo:
The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis
Resumo:
Theory Division Department of Physics