919 resultados para Asymmetric eigenvector maps (AEM)


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Antennas are indispensable component of any wireless communication device. An antenna is a transducer between the transmitter and the free space waves and vice versa. They efficiently transfer electromagnetic energy from a transmission line into free space. But the present day communication applications require compact and ultra wide band designs which cannot be catered by simple microstrip based designs. PIFAs have solved the problem to some extend, but the field of antennas needs more innovative designs In this thesis the design and development of compact planner antenna are presented. Emphasis is given to the design of the feed as well as the radiator resulting in simple compact uniplanar geometries. The Asymmetric coplanar feed used to excite the antennas is found to be a suitable choice for feeding compact antennas.The main objectives of the study are the design of compact single, dual and multi band antennas with uniplanar structure and extension of the design for practical GSM/WLAN applications and Ultra compact antennas using the above techniques and extension of the design to antennas for practical applications like RFID/DVB-H. All the above objectives are thoroughly studied. Antennas with ultra compact dimensions are obtained as a result of the study. Simple equations are provided to design antennas with the required characteristics. The design equations are verified by designing different antennas for different applications.

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We establish numerically the validity of Huberman-Rudnick scaling relation for Lyapunov exponents during the period doubling route to chaos in one dimensional maps. We extend our studies to the context of a combination map. where the scaling index is found to be different.

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An asymmetric coplanar strip-fed uniplanar antenna for wideband applications is presented. The resulting antenna offers a 2:1 VSWR bandwidth greater than 100% from 1.58 to 5.48 GHz covering the DCS/PCS/IEEE 802.11a/WiMAX bands. The antenna has an overall dimension of 44 × 35 mm2 when printed on a substrate of dielectric constant 4.4 and height 1.6 mm. The design equation is also presented in this article. The antenna exhibits good radiation characteristics and moderate gain in the entire operating band.

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A Monte Carlo simulation study of the vacancy-assisted domain growth in asymmetric binary alloys is presented. The system is modeled using a three-state ABV Hamiltonian which includes an asymmetry term. Our simulated system is a stoichiometric two-dimensional binary alloy with a single vacancy which evolves according to the vacancy-atom exchange mechanism. We obtain that, compared to the symmetric case, the ordering process slows down dramatically. Concerning the asymptotic behavior it is algebraic and characterized by the Allen-Cahn growth exponent x51/2. The late stages of the evolution are preceded by a transient regime strongly affected by both the temperature and the degree of asymmetry of the alloy. The results are discussed and compared to those obtained for the symmetric case.

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We have observed a type of giant magnetoresistance (GMR) in magnetic granular Co10Cu90 alloys. The asymmetric GMR depends strongly on the size of magnetic Co particles, which exhibit superparamagnetic behavior at given measured temperature. The asymmetric GMR points to a metastable state that develops when the sample is field-cooled, which is lost after recycling. We propose that high-field cooling produces more effective parallel alignment of small unblocked Co particle moments and interfacial magnetizations, which contributes to the further decrease of the resistance in comparison with the samples zero-field-cooled, and then applied to the same field.

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We study the static properties of the Little model with asymmetric couplings. We show that the thermodynamics of this model coincides with that of the Sherrington-Kirkpatrick model, and we compute the main finite-size corrections to the difference of the free energy between these two models and to some clarifying order parameters. Our results agree with numerical simulations. Numerical results are presented for the symmetric Little model, which show that the same conclusions are also valid in this case.

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The study of simple chaotic maps for non-equilibrium processes in statistical physics has been one of the central themes in the theory of chaotic dynamical systems. Recently, many works have been carried out on deterministic diffusion in spatially extended one-dimensional maps This can be related to real physical systems such as Josephson junctions in the presence of microwave radiation and parametrically driven oscillators. Transport due to chaos is an important problem in Hamiltonian dynamics also. A recent approach is to evaluate the exact diffusion coefficient in terms of the periodic orbits of the system in the form of cycle expansions. But the fact is that the chaotic motion in such spatially extended maps has two complementary aspects- - diffusion and interrnittency. These are related to the time evolution of the probability density function which is approximately Gaussian by central limit theorem. It is noticed that the characteristic function method introduced by Fujisaka and his co-workers is a very powerful tool for analysing both these aspects of chaotic motion. The theory based on characteristic function actually provides a thermodynamic formalism for chaotic systems It can be applied to other types of chaos-induced diffusion also, such as the one arising in statistics of trajectory separation. It was noted that there is a close connection between cycle expansion technique and characteristic function method. It was found that this connection can be exploited to enhance the applicability of the cycle expansion technique. In this way, we found that cycle expansion can be used to analyse the probability density function in chaotic maps. In our research studies we have successfully applied the characteristic function method and cycle expansion technique for analysing some chaotic maps. We introduced in this connection, two classes of chaotic maps with variable shape by generalizing two types of maps well known in literature.

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Bulk and single-particle properties of hot hyperonic matter are studied within the Brueckner-Hartree-Fock approximation extended to finite temperature. The bare interaction in the nucleon sector is the Argonne V18 potential supplemented with an effective three-body force to reproduce the saturating properties of nuclear matter. The modern Nijmegen NSC97e potential is employed for the hyperon-nucleon and hyperon-hyperon interactions. The effect of temperature on the in-medium effective interaction is found to be, in general, very small and the single-particle potentials differ by at most 25% for temperatures in the range from 0 to 60 MeV. The bulk properties of infinite matter of baryons, either nuclear isospin symmetric or a Beta-stable composition that includes a nonzero fraction of hyperons, are obtained. It is found that the presence of hyperons can modify the thermodynamical properties of the system in a non-negligible way.

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The neutron and proton single-particle spectral functions in asymmetric nuclear matter fulfill energy-weighted sum rules. The validity of these sum rules within the self-consistent Green's function approach is investigated. The various contributions to these sum rules and their convergence as a function of energy provide information about correlations induced by the realistic interaction between the nucleons. The study of the sum rules in asymmetric nuclear matter exhibits the isospin dependence of the nucleon-nucleon correlations.

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Starting with logratio biplots for compositional data, which are based on the principle of subcompositional coherence, and then adding weights, as in correspondence analysis, we rediscover Lewi's spectral map and many connections to analyses of two-way tables of non-negative data. Thanks to the weighting, the method also achieves the property of distributional equivalence

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Self-organizing maps (Kohonen 1997) is a type of artificial neural network developed to explore patterns in high-dimensional multivariate data. The conventional version of the algorithm involves the use of Euclidean metric in the process of adaptation of the model vectors, thus rendering in theory a whole methodology incompatible with non-Euclidean geometries. In this contribution we explore the two main aspects of the problem: 1. Whether the conventional approach using Euclidean metric can shed valid results with compositional data. 2. If a modification of the conventional approach replacing vectorial sum and scalar multiplication by the canonical operators in the simplex (i.e. perturbation and powering) can converge to an adequate solution. Preliminary tests showed that both methodologies can be used on compositional data. However, the modified version of the algorithm performs poorer than the conventional version, in particular, when the data is pathological. Moreover, the conventional ap- proach converges faster to a solution, when data is \well-behaved". Key words: Self Organizing Map; Artificial Neural networks; Compositional data

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Wikiloc es un servicio web gratuito para visualizar y compartir rutas y puntos de interés GPS. Utilizando software libre y la API de Google Maps, Wikiloc hace la función de base de datos personal de localizaciones GPS. Desde cualquier acceso a Internet un usuario de GPS puede cargar sus datos GPS y al momento visualizar la ruta y waypoints con distinta cartografía de fondo, incluidos servidores de mapas externos WMS (Web Map Service) o descargarlo a Google Earth para ver en 3D. Paralelamente se muestra el perfil de altura, distancia, desniveles acumulados y las fotos o comentarios que el usuario quiera añadir

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The objective of traffic engineering is to optimize network resource utilization. Although several works have been published about minimizing network resource utilization, few works have focused on LSR (label switched router) label space. This paper proposes an algorithm that takes advantage of the MPLS label stack features in order to reduce the number of labels used in LSPs. Some tunnelling methods and their MPLS implementation drawbacks are also discussed. The described algorithm sets up NHLFE (next hop label forwarding entry) tables in each LSR, creating asymmetric tunnels when possible. Experimental results show that the described algorithm achieves a great reduction factor in the label space. The presented works apply for both types of connections: P2MP (point-to-multipoint) and P2P (point-to-point)

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The aim of traffic engineering is to optimise network resource utilization. Although several works on minimizing network resource utilization have been published, few works have focused on LSR label space. This paper proposes an algorithm that uses MPLS label stack features in order to reduce the number of labels used in LSPs forwarding. Some tunnelling methods and their MPLS implementation drawbacks are also discussed. The algorithm described sets up the NHLFE tables in each LSR, creating asymmetric tunnels when possible. Experimental results show that the algorithm achieves a large reduction factor in the label space. The work presented here applies for both types of connections: P2MP and P2P