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At least 163 records · Page 9

Active control of multi-dimensional random sound in ducts

Previous work has demonstrated how active control may be applied to the control of random noise in ducts. These implementations, however, have been restricted to frequencies where only plane waves are propagating in the duct. In spite of this, the need for this technology at low frequencies has progressed to the point where commercial products that apply these concepts are currently available. Extending the frequency range of this technology requires the extension of current single channel controllers to multi-variate control systems as well as addressing the problems inherent in controlling higher order modes. The application of active control in the multi-dimensional propagation of random noise in waveguides is examined. An adaptive system is implemented using measured system frequency response functions. Experimental results are presented illustrating attained suppressions of 15 to 30 dB for random noise propagating in multiple modes.

Silcox, R. J.↗

A new class of random processes with application to helicopter noise

The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x) (omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

Hardin, Jay C.↗

An introduction to chaotic and random time series analysis

The origin of chaotic behavior and the relation of chaos to randomness are explained. Two mathematical results are described: (1) a representation theorem guarantees the existence of a specific time-domain model for chaos and addresses the relation between chaotic, random, and strictly deterministic processes; (2) a theorem assures that information on the behavior of a physical system in its complete state space can be extracted from time-series data on a single observable. Focus is placed on an important connection between the dynamical state space and an observable time series. These two results lead to a practical deconvolution technique combining standard random process modeling methods with new embedded techniques.

Scargle, Jeffrey D.↗

DS/LPI autocorrelation detection in noise plus random-tone interference

An analysis is presented of a frequency-noncoherent, two-lag autocorrelation statistic for the wideband detection of random binary phase-shift keying (BPSK) signals in noise plus random multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values contrary to an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. The purpose of the paper is to promote the real-time autocorrelation domain and its samples (lags) as a viable approach for detecting random signals in dense environments.

Hinedi, Sami↗

Random field estimation approach to robot dynamics

The difference equations of Kalman filtering and smoothing recursively factor and invert the covariance of the output of a linear state-space system driven by a white-noise process. Here it is shown that similar recursive techniques factor and invert the inertia matrix of a multibody robot system. The random field models are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. They are easier to describe than the models based on classical mechanics, which typically require extensive derivation and manipulation of equations of motion for complex mechanical systems. With the spatially random models, more primitive locally specified computations result in a global collective system behavior equivalent to that obtained with deterministic models. The primary goal of applying random field estimation is to provide a concise analytical foundation for solving robot control and motion planning problems.

Rodriguez, Guillermo↗

Ordering and phase transitions in random-field Ising systems

An exact analysis of the Ising model with infinite-range interactions in a random field and a local mean-field theory in three dimensions is carried out leading to a phase diagram with several coexistence surfaces and lines of critical points. The results show that the phase diagram depends crucially on whether the distribution of random fields is symmetric or not. Thus, Ising-like phase transitions in a porous medium (the asymmetric case) are in a different universality class from the conventional random-field model (symmetric case).

Maritan, Amos↗

Randomization of dust-ejecta motions and the observed morphology of cometary heads

The computer code that has been used over years to study the dust-coma morphology of comets and to generate their synthetic images is upgraded by introducing two categories of random perturbations into the motions of dust particles ejected from discrete sources of activity on the nucleus surface. The new technique is applied to three types of morphological features: multiple concentric halos, a system of spiral jets, and a sunward fan-shaped coma. The results indicate that inclusion of random perturbations substantially enhances the capability for generating synthetic images that faithfully simulate the observed appearance of dust comets. By increasing the magnitude of perturbations in the synthetic images beyond a certain limit, it is possible to 'erase' morphological features characteristic of the ejection process. This implies that the lack of distinct morphology in the head of a comet cannot be interpreted as the absence of discrete sources of activity on the nucleus surface. The effects of varying random perturbations on the appearance of the computer-generated images are investigated in detail and the suspected major role that imperfect flow collimation (or flow divergence) in dust jets plays with regard to the observed coma morphology is discussed.

Sekanina, Zdenek↗

Spatio-temporal contextual classification based on Markov random field model

A contextural classifier based on a Markov random field model, which can utilize both spatial and temporal contexts, is investigated. Spatial and temporal neighbors are defined, and the class assignment of each pixel is assumed to be dependent only on the measurement vectors of itself and those of its spatial and temporal neighbors according to the Markov random field property. Only interpixel class dependency context is used in the classification. The joint prior probability of the classes of each pixel and its spatial and temporal neighbors are modeled by a Gibbs random field. The classification is performed in a recursive manner. Experiments with multi-temporal Thematic Mapper data show promising results.

Jeon, Byeungwoo↗

Scattering from randomly oriented scatterers with strong permittivity fluctuations

Strong permittivity fluctuation theory is used to solve the problem of scattering from a medium composed of completely randomly oriented scatterers under a low frequency limit. Gaussian statistics are not assumed for the renormalized scattering sources. Numerical results on effective permittivity are illustrated for oblate and prolate spheroidal scatterers and compared with the results for spherical scatterers. The results are consistent with discrete scatterer theory. The effective permittivity of a random medium embedded with nonspherical scatterers shows a higher imaginary part than the spherical scatterer case with equal correlation volume. Under the distorted Born approximation, the polarimetric covariance matrix for the backscattered electric field is calculated for half-space randomly oriented scatterers. The nonspherical geometry of the scatterers shows significant effects on the cross-polarized backscattering returns, and the correlation coefficient between HH and VV returns. The polarimetric backscattering coefficients can provide useful information in distinguishing the geometry of scatterers.

Yueh, S. H.↗

Randomization in robot tasks

This paper investigates the role of randomization in the solution of robot manipulation tasks. One example of randomization is shown by the strategy of shaking a bin holding a part in order to orient the part in a desired stable state with some high probability. Randomization can be useful for mobile robot navigation and as a means of guiding the design process.

Erdmann, Michael↗

A statistical analysis of mesoscale rainfall as a random cascade

The paper considers the random cascade theory for spatial rainfall. Particular attention was given to the following four areas: (1) the relationship of the random cascade theory of rainfall to the simple scaling and the hierarchical cluster-point-process theories, (2) the mathematical foundations for some of the formalisms commonly applied in the develpment of statistical cascade theory, (3) the empirical evidence for a random cascade theory of rainfall, and (4) the way of using data for making estimates of parameters and for making statistical inference within this theoretical framework. An analysis of space-time rainfall data is presented. Cascade simulations are carried out to provide a comparison with methods of analysis that are applied to the rainfall data.

Gupta, Vijay K.↗

Gravitational microlensing - The effect of random motion of individual stars in the lensing galaxy

We investigate the influence of random motion of individual stars in the lensing galaxy on the light curve of a gravitationally lensed background quasar. We compare this with the effects of the transverse motion of the galaxy. We find that three-dimensional random motion of stars with a velocity dispersion sigma in each dimension is more effective in producing 'peaks' in a microlensed light curve by a factor a about 1.3 than motion of the galaxy with a transverse velocity v(t) = sigma. This effectiveness parameter a seems to depend only weakly on the surface mass density. With an assumed transverse velocity of v(t) = 600 km/s of the galaxy lensing the QSO 2237+0305 and a measured velocity dispersion of sigma = 215 km/s, the expected rate of maxima in the light curves calculated for bulk motion alone has to be increased by about 10 percent due to the random motion of stars. As a consequence, the average time interval Delta t between two high-magnification events is smaller than the time interval Delta(t) bulk, calculated for bulk motion alone, Delta t about 0.9 Delta(t) bulk.

Kundic, Tomislav↗

A finite element large deflection random response of a pipe containing fluid flow

A finite element approach is developed for beam type pipes undergoing large deflections subjected to random loadings. The influence of fluid velocity on the random response is investigated. The root-mean-square (rms) deflections and frequencies for different sound spectrum level values are determined for pipes with both ends either simply supported or clamped. The required number of modes to achieve accurate rms deflections is studied. The prediction of fatigue life is then based on the maximum rms stress. This analytical investigation will help to broaden the basic understanding of the role of fluid flow within structures subjected to random excitations.

Chiang, C. K.↗

Light scattering by size-shape distributions of randomly oriented axially symmetric particles of a size comparable to a wavelength

Rigorously light scattering by size-shape distributions of randomly oriented axially symmetric particles are calculated by the T-matrix method, as extended to randomly oriented scatterers. The computational scheme is described along with a newly developed convergence procedure that makes it possible to substantially reduce computer time and storage requirements. The elements of the Stokes scattering matrix for a power-law size distribution of randomly oriented moderately aspherical spheroids are shown to be much smoother than and differ substantially from those of equivalent monodisperse spheroids; averaging over orientations does not eliminate the necessity of averaging over particle sizes. The angular-scattering behavior of the ensembles of nonspherical particles is found to be significantly different from that of the equivalent polydisperse spheres.

Mishchenko, Michael I.↗

Application of the target decomposition theorem to a polarimetric random media model

With advances in polarimetric radar measurements of land surfaces, the need for understanding the underlying scattering mechanisms and dominant target features has become the focus of many studies. In particular, the maximum use of the polarimetric information to identify and/or separate parameters related to the surface features such as vegetation thickness, structure, water content, and soil surface characteristics will enhance the possibility of using polarimetric radars for monitoring the earth's surface from space. In this paper, Cloude's decomposition theorem is applied to a polarimetric random media model to simulate the radar measurements of vegetated canopies. The vegetated canopies are modeled as a three layer discrete random medium with leaves and branches in the first layer, tree trunks in the second layer, and a half space of homogeneous ground with rough interface as the bottom layer. The distorted born approximation (DBA) has been used to compute full Mueller matrix of the canopy, using canonical dielectric objects such as thin discs and cylinders as leaves, branches, and trunks, respectively. The Mueller matrix and the derived covariance matrix contain information on the second order statistics of radar signals at various polarizations from the canopy. To decompose the covariance matrix to its constituent targets, the eigenvalues and eigenvectors of the covariance matrix are computed in terms of the physical parameters of the canopy. In addition, each eigenvector explicitly shows the scattering mechanisms such as odd and even reflections in the canopy. Cloude's decomposition theorem is applied using the Pauli spin matrices as a basis and an expression for the degree of disorder or the entropy for the vegetated surface is found. Then, the physical parameters estimated from in situ measurements are used in the random media to obtain realistic covariance matrices. As a result, the sensitivity of the eigenvalue spectrums and the coefficients resulting from the target decomposition theorem to the physical parameters of the canopy are examined and the possible use of Cloude's theorem to estimate vegetation and soil parameters is discussed.

Saatchi, Sasan S.↗

On the minimum of independent geometrically distributed random variables

The expectations E(X(sub 1)), E(Z(sub 1)), and E(Y(sub 1)) of the minimum of n independent geometric, modifies geometric, or exponential random variables with matching expectations differ. We show how this is accounted for by stochastic variability and how E(X(sub 1))/E(Y(sub 1)) equals the expected number of ties at the minimum for the geometric random variables. We then introduce the 'shifted geometric distribution' and show that there is a unique value of the shift for which the individual shifted geometric and exponential random variables match expectations both individually and in the minimums.

Ciardo, Gianfranco↗

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

Over, Thomas, M.↗

Effect of the degree of disorder on electronic and optical properties in random superlattices

A three-dimensional tight-binding calculation is developed and used to study disorder effects in a realistic random superlattice. With increasing disorder, a tendency of possible indirect-direct band-gap transition is suggested. Direct evidence of mobility edges between localized and extended states in three-dimensional random systems is given. As system disorder increases, the optical absorption intensities increase dramatically from five to forty-five times stronger than the ordered (GaAs)(sub 1)/(AlAs)(sub 1) superlattice. It is believed that the degree of disorder significantly affects electronic and optical properties of GaAs/AlAs random superlattices.

Wang, E. G.↗