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At least 19 records

A new class of gradient estimators for queueing systems with real-time constraints

Queuing systems are considered where the waiting or sojourn times of customers are constrained by specified deadlines. A performance measure of interest in these systems is the probability that a customer exceeds its assigned deadline. A new class of gradient estimators is presented for such performance measures with respect to various system parameters. The approach is applicable to a general class of problems and is based on efficiently capturing sensitivity information for probabilities of event occurrences from observed sample paths.

Gong, Wei-Bo

Sea Surface Temperature Gradients Estimation Using Top-of-Atmosphere Observations from the ESA Earth Explorer 10 Harmony Mission: Preliminary Studies

The Harmony satellite mission was recently approved as the next European Space Agency (ESA) Earth Explorer 10. The mission science objectives cover several applications related to solid earth, the cryosphere, upper-ocean dynamics and air–sea interactions. The mission consists of a constellation of two satellites, flying with the Copernicus Sentinel 1 (C or D) spacecraft, each hosting a C-band receive-only radar and a thermal infrared (TIR) payload. From an ocean dynamics/air–sea interaction perspective, the mission will provide the unique opportunity to observe simultaneously the signature of submesoscale upper-ocean processes via synthetic aperture radar and TIR imagery. The TIR imager is based on microbolometer technology and its acquisitions will rely on four channels: three narrow-band channels yielding observations at a ≃1 km spatial sampling distance (SSD) and a panchromatic (PAN, 8–12 μm) channel characterized by a ≃300 m SSD. Our study investigates the potential of Harmony in retrieving spatial features related to sea surface temperature (SST) gradients from the high-resolution PAN channel, relying on top-of-atmosphere (TOA) observations. Compared to a standard SST gradient retrieval, our approach does not require atmospheric correction, thus avoiding uncertainties due to inter-channel co-registration and radiometric consistency, with the possibility of exploiting the higher resolution of the PAN channel. The investigations were carried out simulating the future Harmony TOA radiances (TARs), as well as relying on existing state-of-the-art level 1 satellite products. Our approach enables the correct description of SST features at the sea surface avoiding the generation of spurious features due to atmospheric correction and/or instrumental issues. In addition, analyses based on existing satellite products suggest that the clear-sky TOA observations, in a typical mid-latitude scene, allow the reconstruction of up to 85% of the gradient magnitudes found at the sea-surface level. The methodology is less efficient in tropical areas, suffering from smoothing effects due to the high concentrations of water vapor.

sea surface temperature (SST)

Gradient estimates from stereo measurements for a Martian vehicle

The Martian roving vehicle requires an autonomous obstacle detection and path selection system. A laser range finder will be used to determine the locations of a number of discrete points at distances of 3 to 30 meters from the vehicle. The system might measure angles, ranges or a combination of both types of measurements.

Pfeifer, W. J.

The effect of turbulence on atmospheric gradient parameters estimated from ground-based radiometric and space geodetic measurements

A straightforward expression for the covariance of a general vector of atmospheric parameters is employed to calculate the effects of estimates of spatial gradients for a frozen Kolmogorov turbulence field moving over a site at constant velocities. Numerical calculations are performed to investigate the implications for three techniques: ground-based microwave radiometry, geodesy with the Global Positioning System, and VLBI. It is found that a prevailing wind with no true static gradients may give rise to apparent azimuthal asymmetries when gradient parameters are estimated. The standard deviation of the estimated north gradient parameter as a function of wind direction, for various wind speeds, is illustrated.

Davis, James L.

Stochastic estimates of gradient from laser measurements for an autonomous Martian roving vehicle

The general problem of estimating the state vector x from the state equation h = Ax where h, A, and x are all stochastic, is presented. Specifically, the problem is for an autonomous Martian roving vehicle to utilize laser measurements in estimating the gradient of the terrain. Error exists due to two factors - surface roughness and instrumental measurements. The errors in slope depend on the standard deviations of these noise factors. Numerically, the error in gradient is expressed as a function of instrumental inaccuracies. Certain guidelines for the accuracy of permissable gradient must be set. It is found that present technology can meet these guidelines.

Burger, P. A.

Stochastic estimates of gradient from laser measurements for an autonomous Martian Roving Vehicle

The general problem presented in this paper is one of estimating the state vector x from the state equation h = Ax, where h, A, and x are all stochastic. Specifically, the problem is for an autonomous Martian Roving Vehicle to utilize laser measurements in estimating the gradient of the terrain. Error exists due to two factors - surface roughness and instrumental measurements. The errors in slope depend on the standard deviations of these noise factors. Numerically, the error in gradient is expressed as a function of instrumental inaccuracies. Certain guidelines for the accuracy of permissable gradient must be set. It is found that present technology can meet these guidelines.-

Shen, C. N.

Derivative-free stochastic optimization via adaptive sampling strategies

In this paper, we present a novel derivative-free framework for solving unconstrained stochastic optimization problems. Many problems in fields ranging from simulation optimization to reinforcement learning to quantum computing involve settings where only stochastic function values are obtained via a zeroth-order oracle, which has no available gradient information and necessitates the usage of derivative-free optimization methodologies. Our approach includes estimating gradients using stochastic function evaluations and integrating adaptive sampling techniques to control the accuracy in these stochastic approximations. Our framework encapsulates several gradient estimation techniques, including standard finite-difference, Gaussian smoothing, sphere smoothing, randomized coordinate finite-difference, and randomized subspace finite-difference methods. We provide theoretical convergence guarantees for our framework and analyze the worst-case iteration and sample complexities associated with each gradient estimation method. Finally, we demonstrate the empirical performance of the methods on logistic regression and nonlinear least squares problems.

Adaptive sampling

Peak-Seeking Control Using Gradient and Hessian Estimates

A peak-seeking control method is presented which utilizes a linear time-varying Kalman filter. Performance function coordinate and magnitude measurements are used by the Kalman filter to estimate the gradient and Hessian of the performance function. The gradient and Hessian are used to command the system toward a local extremum. The method is naturally applied to multiple-input multiple-output systems. Applications of this technique to a single-input single-output example and a two-input one-output example are presented.

Ryan, John J.

Perturbation analysis of queueing systems with a time-varying arrival rate

The authors consider an M/G/1 queuing with a time-varying arrival rate. The objective is to obtain infinitesimal perturbation analysis (IPA) gradient estimates for various performance measures of interest with respect to certain system parameters. In particular, the authors consider the mean system time over n arrivals and an arrival rate alternating between two values. By choosing a convenient sample path representation of this system, they derive an unbiased IPA gradient estimator which, however, is not consistent, and investigate the nature of this problem.

Cassandras, Christos G.

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

AMSU-A Tropical Cyclone Maximum Sustained Winds and Web Site

The Advanced Microwave Sounding Unit (AMSU)-A instruments on the NOAA-15 and NOAA-16 satellites provide information on the warm cores of tropical cyclones from oxygen channel brightness temperature (Tb) measurements near 55 GHz. With appropriate assumptions, cyclone-scale Tb gradients can be directly related to middle-to-lower tropospheric height gradients. We have developed a method for diagnosis of maximum sustained winds (Vmax) from radially averaged Tb gradients in several of the AMSU channels. Calibration of the method with recon-based (or other in situ) winds results in better agreement than with Dvorak wind estimates. Gradient wind theory shows that the warm core Tb gradient signal increases non-linearly with wind speed, making microwave temperature sounders useful for diagnosing high wind speeds, but at the expense of a minimum useful detection limit of about 40 knots. It is found that accurate wind diagnoses depend upon (1) accounting for hydrometeor effects in the AMSU channels, and (2) maximizing signal-to-noise, since the 50 km resolution data cannot fully resolve the temperature gradients in the Vmax region, typically 10-20 km in scale. AMSU imagery and max diagnoses from specific hurricanes will be shown, including independent tests from the 2000 hurricane season.

Spencer, Roy

Automated remote sensing of sea ice using synthetic aperture radar

Two techniques for automated sea ice tracking: image pyramids (hierarchical correlation) and feature tracking were applied to a pair of SEASAT SAR sea ice images. The results compare well with each other and manually tracked estimates of the ice velocity field. Refinement of the image pyramid technique should include removal of a small number of erroneous velocity vectors using constraints dependent on correlation coefficient, near neighbor velocities, and velocity gradients. Estimates of sea ice velocity are successfully obtained over limited areas using the boundary segment tracking technique. Refinement of the feature tracking technique should include use of pressure ridge features, constrained search, and relaxation techniques.

Vesecky, J. F.

System identification computational considerations.

System identification methods may be accurately characterized as inverse computational problems. Three approaches to the computational problem are considered. Equation error methods are based on regression analysis techniques. Attention is given to the maximum conditional likelihood estimate and the maximum unconditional likelihood (Bayesian) estimate. Gradient dependent algorithms for solving the minimization problems are discussed, taking into account Gaussian methods, quadratic model methods, and the homogeneous function model method of Jacobson and Oksman. Some advanced methods are also examined.

Bowles, R. L.

Data acquisition and path selection decision making for an autonomous roving vehicle

The feasibility of using range/pointing angle data such as might be obtained by a laser rangefinder for the purpose of terrain evaluation in the 10-40 meter range on which to base the guidance of an autonomous rover was investigated. The decision procedure of the rapid estimation scheme for the detection of discrete obstacles has been modified to reinforce the detection ability. With the introduction of the logarithmic scanning scheme and obstacle identification scheme, previously developed algorithms are combined to demonstrate the overall performance of the intergrated route designation system using laser rangefinder. In an attempt to cover a greater range, 30 m to 100 mm, the problem estimating gradients in the presence of positioning angle noise at middle range is investigated.

Shen, C. N.

The effect of model uncertainty on some optimal routing problems

The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.

Mohanty, Bibhu

VLBI Contribution to ITRF2000

The VLBI data set spanning Aug. 1919 to the present is a major constituent of ITRF2000 because of the time span, the geometric strength and the accuracy of the modeling. Formal velocity errors for the best stations are less than 0.3 mm/yr while the probable frame definition error for station velocities is approximately 0.4 mm/yr. The primary systematic errors are the troposphere and tidal loading (solid Earth and ocean). However, the scale of the VLBI TRF is probably only weakly affected because of continued improvements in the tropospheric mapping function and gradient estimation. There are some weaknesses in the spatial distribution of data, particularly in the southern hemisphere, and the quality of the mobile VLBI results is now suboptimal. The deployment of the TIGO system to Chile will improve the geometric coverage. The current state of the art of VLBI analysis will be discussed.

Ma, Chopo

Intelligent Control for Drag Reduction on the X-48B Vehicle

This paper focuses on the development of an intelligent control technology for in-flight drag reduction. The system is integrated with and demonstrated on the full X-48B nonlinear simulation. The intelligent control system utilizes a peak-seeking control method implemented with a time-varying Kalman filter. Performance functional coordinate and magnitude measurements, or independent and dependent parameters respectively, are used by the Kalman filter to provide the system with gradient estimates of the designed performance function which is used to drive the system toward a local minimum in a steepestdescent approach. To ensure ease of integration and algorithm performance, a single-input single-output approach was chosen. The framework, specific implementation considerations, simulation results, and flight feasibility issues related to this platform are discussed.

Griffin, Brian Joseph