194 resultados para SINGULAR CONTINUOUS-SPECTRUM


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Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms of current interest. Since its inception in the mid 1990s, DE has been finding many successful applications in real-world optimization problems from diverse domains of science and engineering. This paper takes a first significant step toward the convergence analysis of a canonical DE (DE/rand/1/bin) algorithm. It first deduces a time-recursive relationship for the probability density function (PDF) of the trial solutions, taking into consideration the DE-type mutation, crossover, and selection mechanisms. Then, by applying the concepts of Lyapunov stability theorems, it shows that as time approaches infinity, the PDF of the trial solutions concentrates narrowly around the global optimum of the objective function, assuming the shape of a Dirac delta distribution. Asymptotic convergence behavior of the population PDF is established by constructing a Lyapunov functional based on the PDF and showing that it monotonically decreases with time. The analysis is applicable to a class of continuous and real-valued objective functions that possesses a unique global optimum (but may have multiple local optima). Theoretical results have been substantiated with relevant computer simulations.

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Pulse retardation method of Breit and Tuve has been modified to record continuously the equivalent height as well as the intensity of reflections from the ionosphere. Synchronized pulses are transmitted, and the received ground pulse and the reflected pulses, after amplification and suitable distortion, are applied to the focusing cylinder of a cathode ray tube the horizontal deflecting plates of which are connected to a synchronized linear time base circuit. The pattern on the screen is composed of a bright straight line corresponding to the time base with dark gaps corresponding to the received pulses. The distance between the initial points of the gaps represents retardation while the widths of the gaps correspond to the intensity of the pulses. The pattern is photographed on a vertically moving film. One of the first few records taken at Bangalore on 4 megacycles is reproduced. It shows, among other things, that the less retarded component of magneto-ionic splitting from the F layer is present most of the time. Whenever the longer retardation component does occur, it has stronger intensity than the former. Towards the late evening hours, just before disappearing, when the F layer rises and exhibits magnetoionic splitting, the intensity of the less retarded component is extremely low compared with the other component.

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The spectral index-luminosity relationship for steep-spectrum cores in galaxies and quasars has been investigated, and it is found that the sample of galaxies supports earlier suggestions of a strong correlation, while there is weak evidence for a similar relationship for the quasars. It is shown that a strong spectral index-luminosity correlation can be used to set an upper limit to the velocities of the radio-emitting material which is expelled from the nucleus in the form of collimated beams or jets having relativistic bulk velocities. The data on cores in galaxies indicate that the Lorentz factors of the radiating material are less than about 2.

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The critical behaviour has been investigated in single crystalline Nd0.6Pb0.4MnO3 near the paramagnetic to ferromagnetic transition temperature (TC) by static magnetic measurements. The values of TC and the critical exponents β, γ and δ are estimated by analysing the data in the critical region. The exponent values are very close to those expected for 3D Heisenberg ferromagnets with short-range interactions. Specific heat measurements show a broad cusp at TC (i.e., exponent α<0) being consistent with Heisenberg-like behaviour.

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The repeated or closely spaced eigenvalues and corresponding eigenvectors of a matrix are usually very sensitive to a perturbation of the matrix, which makes capturing the behavior of these eigenpairs very difficult. Similar difficulty is encountered in solving the random eigenvalue problem when a matrix with random elements has a set of clustered eigenvalues in its mean. In addition, the methods to solve the random eigenvalue problem often differ in characterizing the problem, which leads to different interpretations of the solution. Thus, the solutions obtained from different methods become mathematically incomparable. These two issues, the difficulty of solving and the non-unique characterization, are addressed here. A different approach is used where instead of tracking a few individual eigenpairs, the corresponding invariant subspace is tracked. The spectral stochastic finite element method is used for analysis, where the polynomial chaos expansion is used to represent the random eigenvalues and eigenvectors. However, the main concept of tracking the invariant subspace remains mostly independent of any such representation. The approach is successfully implemented in response prediction of a system with repeated natural frequencies. It is found that tracking only an invariant subspace could be sufficient to build a modal-based reduced-order model of the system. Copyright (C) 2012 John Wiley & Sons, Ltd.

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A CMOS gas sensor array platform with digital read-out containing 27 sensor pixels and a reference pixel is presented. A signal conditioning circuit at each pixel includes digitally programmable gain stages for sensor signal amplification followed by a second order continuous time delta sigma modulator for digitization. Each sensor pixel can be functionalized with a distinct sensing material that facilitates transduction based on impedance change. Impedance spectrum (up to 10 KHz) of the sensor is obtained off-chip by computing the fast Fourier transform of sensor and reference pixel outputs. The reference pixel also compensates for the phase shift introduced by the signal processing circuits. The chip also contains a temperature sensor with digital readout for ambient temperature measurement. A sensor pixel is functionalized with polycarbazole conducting polymer for sensing volatile organic gases and measurement results are presented. The chip is fabricated in a 0.35 CMOS technology and requires a single step post processing for functionalization. It consumes 57 mW from a 3.3 V supply.

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NMR spectroscopic chiral visualization, unambiguous assignment of peaks pertaining to R and S enantiomers and the subsequent measurement of enantiomeric composition demands a highly resolved spectrum. The method fails when the spectrum is severely overcrowded or highly complex, thereby hampering the determination of enantiomeric excess. In order to circumvent such problems we propose the utility of pure shift spectrum obtained by resolving the chemical shift and coupling information in two orthogonal dimensions. The skew projected spectrum yields singlet's at the respective chemical shift positions, permitting the unravelling of the superimposed spectral transitions for each enantiomer and measurement of enantiomeric composition. (C) 2012 Elsevier B. V. All rights reserved.

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This paper presents a singular edge-based smoothed finite element method (sES-FEM) for mechanics problems with singular stress fields of arbitrary order. The sES-FEM uses a basic mesh of three-noded linear triangular (T3) elements and a special layer of five-noded singular triangular elements (sT5) connected to the singular-point of the stress field. The sT5 element has an additional node on each of the two edges connected to the singular-point. It allows us to represent simple and efficient enrichment with desired terms for the displacement field near the singular-point with the satisfaction of partition-of-unity property. The stiffness matrix of the discretized system is then obtained using the assumed displacement values (not the derivatives) over smoothing domains associated with the edges of elements. An adaptive procedure for the sES-FEM is proposed to enhance the quality of the solution with minimized number of nodes. Several numerical examples are provided to validate the reliability of the present sES-FEM method. (C) 2012 Elsevier B.V. All rights reserved.

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This paper analyzes the error exponents in Bayesian decentralized spectrum sensing, i.e., the detection of occupancy of the primary spectrum by a cognitive radio, with probability of error as the performance metric. At the individual sensors, the error exponents of a Central Limit Theorem (CLT) based detection scheme are analyzed. At the fusion center, a K-out-of-N rule is employed to arrive at the overall decision. It is shown that, in the presence of fading, for a fixed number of sensors, the error exponents with respect to the number of observations at both the individual sensors as well as at the fusion center are zero. This motivates the development of the error exponent with a certain probability as a novel metric that can be used to compare different detection schemes in the presence of fading. The metric is useful, for example, in answering the question of whether to sense for a pilot tone in a narrow band (and suffer Rayleigh fading) or to sense the entire wide-band signal (and suffer log-normal shadowing), in terms of the error exponent performance. The error exponents with a certain probability at both the individual sensors and at the fusion center are derived, with both Rayleigh as well as log-normal shadow fading. Numerical results are used to illustrate and provide a visual feel for the theoretical expressions obtained.

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This paper proposes an algorithm for joint data detection and tracking of the dominant singular mode of a time varying channel at the transmitter and receiver of a time division duplex multiple input multiple output beamforming system. The method proposed is a modified expectation maximization algorithm which utilizes an initial estimate to track the dominant modes of the channel at the transmitter and the receiver blindly; and simultaneously detects the un known data. Furthermore, the estimates are constrained to be within a confidence interval of the previous estimate in order to improve the tracking performance and mitigate the effect of error propagation. Monte-Carlo simulation results of the symbol error rate and the mean square inner product between the estimated and the true singular vector are plotted to show the performance benefits offered by the proposed method compared to existing techniques.

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We consider cooperative spectrum sensing for cognitive radios. We develop an energy efficient detector with low detection delay using sequential hypothesis testing. Sequential Probability Ratio Test (SPRT) is used at both the local nodes and the fusion center. We also analyse the performance of this algorithm and compare with the simulations. Modelling uncertainties in the distribution parameters are considered. Slow fading with and without perfect channel state information at the cognitive radios is taken into account.

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This paper considers cooperative spectrum sensing in Cognitive Radios. In our previous work we have developed DualSPRT, a distributed algorithm for cooperative spectrum sensing using Sequential Probability Ratio Test (SPRT) at the Cognitive Radios as well as at the fusion center. This algorithm works well, but is not optimal. In this paper we propose an improved algorithm- SPRT-CSPRT, which is motivated from Cumulative Sum Procedures (CUSUM). We analyse it theoretically. We also modify this algorithm to handle uncertainties in SNR's and fading.