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At least 415 records · Page 23

Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics

The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.

Fijany, Amir↗

Performance analysis of structured gradient algorithm

The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained least-mean-square (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.

Godara, Lal C.↗

Object-oriented feature-tracking algorithms for SAR images of the marginal ice zone

An unsupervised method that chooses and applies the most appropriate tracking algorithm from among different sea-ice tracking algorithms is reported. In contrast to current unsupervised methods, this method chooses and applies an algorithm by partially examining a sequential image pair to draw inferences about what was examined. Based on these inferences the reported method subsequently chooses which algorithm to apply to specific areas of the image pair where that algorithm should work best.

Daida, Jason↗

Strategies for concurrent processing of complex algorithms in data driven architectures

Performance modeling and performance enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures are discussed. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called algorithm to architecture mapping model (ATAMM). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Som, Sukhamoy↗

A Parallel Rendering Algorithm for MIMD Architectures

Applications such as animation and scientific visualization demand high performance rendering of complex three dimensional scenes. To deliver the necessary rendering rates, highly parallel hardware architectures are required. The challenge is then to design algorithms and software which effectively use the hardware parallelism. A rendering algorithm targeted to distributed memory MIMD architectures is described. For maximum performance, the algorithm exploits both object-level and pixel-level parallelism. The behavior of the algorithm is examined both analytically and experimentally. Its performance for large numbers of processors is found to be limited primarily by communication overheads. An experimental implementation for the Intel iPSC/860 shows increasing performance from 1 to 128 processors across a wide range of scene complexities. It is shown that minimal modifications to the algorithm will adapt it for use on shared memory architectures as well.

Crockett, Thomas W.↗

Algorithm and code development for unsteady three-dimensional Navier-Stokes equations

A streamwise upwind algorithm for solving the unsteady 3-D Navier-Stokes equations was extended to handle the moving grid system. It is noted that the finite volume concept is essential to extend the algorithm. The resulting algorithm is conservative for any motion of the coordinate system. Two extensions to an implicit method were considered and the implicit extension that makes the algorithm computationally efficient is implemented into Ames's aeroelasticity code, ENSAERO. The new flow solver has been validated through the solution of test problems. Test cases include three-dimensional problems with fixed and moving grids. The first test case shown is an unsteady viscous flow over an F-5 wing, while the second test considers the motion of the leading edge vortex as well as the motion of the shock wave for a clipped delta wing. The resulting algorithm has been implemented into ENSAERO. The upwind version leads to higher accuracy in both steady and unsteady computations than the previously used central-difference method does, while the increase in the computational time is small.

Obayashi, Shigeru↗

Selection of optimum median-filter-based ambiguity removal algorithm parameters for NSCAT

The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.

Shaffer, Scott↗

A predictor-corrector guidance algorithm for use in high-energy aerobraking system studies

A three-degree-of-freedom predictor-corrector guidance algorithm has been developed specifically for use in high-energy aerobraking performance evaluations. The present study reports on both the development and capabilities of this guidance algorithm to the design of manned Mars aero-braking vehicles. Atmospheric simulations are performed to demonstrate the applicability of this algorithm and to evaluate the effect of atmospheric uncertainties upon the mission requirements. The off-nominal conditions simulated result from atmospheric density and aerodynamic characteristic mispredictions. The guidance algorithm is also used to provide relief from the high deceleration levels typically encountered in a high-energy aerobraking mission profile. Through this analysis, bank-angle modulation is shown to be an effective means of providing deceleration relief. Furthermore, the capability of the guidance algorithm to manage off-nominal vehicle aerodynamic and atmospheric density variations is demonstrated.

Braun, Robert D.↗

Improved algorithms for mapping pipelined and parallel computations

Recent work on the problem of mapping pipelined or parallel computations onto linear array, shared memory, and host-satellite systems is extended. It is shown how these problems can be solved even more efficiently when computation module execution times are bounded from below, intermodule communication times are bounded from above, and the processors satisfy certain homogeneity constraints. The improved algorithms have significantly lower time and space complexities than the more general algorithms: in one case, an O(nm3) time algorithm for mapping m modules onto n processors is replaced with an O(nm log m) time algorithm, and the space requirements are reduced from O(nm2) to O(m). Run-time complexity is reduced further with parallel mapping algorithms based on these improvements, which run on the architectures for which they create mappings.

Nicol, David M.↗

An implementation of the look-ahead Lanczos algorithm for non-Hermitian matrices, part 2

It is shown how the look-ahead Lanczos process (combined with a quasi-minimal residual QMR) approach) can be used to develop a robust black box solver for large sparse non-Hermitian linear systems. Details of an implementation of the resulting QMR algorithm are presented. It is demonstrated that the QMR method is closely related to the biconjugate gradient (BCG) algorithm; however, unlike BCG, the QMR algorithm has smooth convergence curves and good numerical properties. We report numerical experiments with our implementation of the look-ahead Lanczos algorithm, both for eigenvalue problem and linear systems. Also, program listings of FORTRAN implementations of the look-ahead algorithm and the QMR method are included.

Freund, Roland W.↗

Intelligent perturbation algorithms for space scheduling optimization

Intelligent perturbation algorithms for space scheduling optimization are presented in the form of the viewgraphs. The following subject areas are covered: optimization of planning, scheduling, and manifesting; searching a discrete configuration space; heuristic algorithms used for optimization; use of heuristic methods on a sample scheduling problem; intelligent perturbation algorithms are iterative refinement techniques; properties of a good iterative search operator; dispatching examples of intelligent perturbation algorithm and perturbation operator attributes; scheduling implementations using intelligent perturbation algorithms; major advances in scheduling capabilities; the prototype ISF (industrial Space Facility) experiment scheduler; optimized schedule (max revenue); multi-variable optimization; Space Station design reference mission scheduling; ISF-TDRSS command scheduling demonstration; and example task - communications check.

Kurtzman, Clifford R.↗

Real-time demonstration hardware for enhanced DPCM video compression algorithm

The lack of available wideband digital links as well as the complexity of implementation of bandwidth efficient digital video CODECs (encoder/decoder) has worked to keep the cost of digital television transmission too high to compete with analog methods. Terrestrial and satellite video service providers, however, are now recognizing the potential gains that digital video compression offers and are proposing to incorporate compression systems to increase the number of available program channels. NASA is similarly recognizing the benefits of and trend toward digital video compression techniques for transmission of high quality video from space and therefore, has developed a digital television bandwidth compression algorithm to process standard National Television Systems Committee (NTSC) composite color television signals. The algorithm is based on differential pulse code modulation (DPCM), but additionally utilizes a non-adaptive predictor, non-uniform quantizer and multilevel Huffman coder to reduce the data rate substantially below that achievable with straight DPCM. The non-adaptive predictor and multilevel Huffman coder combine to set this technique apart from other DPCM encoding algorithms. All processing is done on a intra-field basis to prevent motion degradation and minimize hardware complexity. Computer simulations have shown the algorithm will produce broadcast quality reconstructed video at an average transmission rate of 1.8 bits/pixel. Hardware implementation of the DPCM circuit, non-adaptive predictor and non-uniform quantizer has been completed, providing realtime demonstration of the image quality at full video rates. Video sampling/reconstruction circuits have also been constructed to accomplish the analog video processing necessary for the real-time demonstration. Performance results for the completed hardware compare favorably with simulation results. Hardware implementation of the multilevel Huffman encoder/decoder is currently under development along with implementation of a buffer control algorithm to accommodate the variable data rate output of the multilevel Huffman encoder. A video CODEC of this type could be used to compress NTSC color television signals where high quality reconstruction is desirable (e.g., Space Station video transmission, transmission direct-to-the-home via direct broadcast satellite systems or cable television distribution to system headends and direct-to-the-home).

Bizon, Thomas P.↗

Thrust stand evaluation of engine performance improvement algorithms in an F-15 airplane

An investigation is underway to determine the benefits of a new propulsion system optimization algorithm in an F-15 airplane. The performance seeking control (PSC) algorithm optimizes the quasi-steady-state performance of an F100 derivative turbofan engine for several modes of operation. The PSC algorithm uses an onboard software engine model that calculates thrust, stall margin, and other unmeasured variables for use in the optimization. As part of the PSC test program, the F-15 aircraft was operated on a horizontal thrust stand. Thrust was measured with highly accurate load cells. The measured thrust was compared to onboard model estimates and to results from posttest performance programs. Thrust changes using the various PSC modes were recorded. Those results were compared to benefits using the less complex highly integrated digital electronic control (HIDEC) algorithm. The PSC maximum thrust mode increased intermediate power thrust by 10 percent. The PSC engine model did very well at estimating measured thrust and closely followed the transients during optimization. Quantitative results from the evaluation of the algorithms and performance calculation models are included with emphasis on measured thrust results. The report presents a description of the PSC system and a discussion of factors affecting the accuracy of the thrust stand load measurements.

Conners, Timothy R.↗

Problem solving with genetic algorithms and Splicer

Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.

Bayer, Steven E.↗

NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager - Comparison with Landsat satellite imagery

The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.

Steffen, Konrad↗

A VLSI architecture for simplified arithmetic Fourier transform algorithm

The arithmetic Fourier transform (AFT) is a number-theoretic approach to Fourier analysis which has been shown to perform competitively with the classical FFT in terms of accuracy, complexity, and speed. Theorems developed in a previous paper for the AFT algorithm are used here to derive the original AFT algorithm which Bruns found in 1903. This is shown to yield an algorithm of less complexity and of improved performance over certain recent AFT algorithms. A VLSI architecture is suggested for this simplified AFT algorithm. This architecture uses a butterfly structure which reduces the number of additions by 25 percent of that used in the direct method.

Reed, Irving S.↗

Optimal parallel algorithms for problems modeled by a family of intervals

A family of intervals on the real line provides a natural model for a vast number of scheduling and VLSI problems. Recently, a number of parallel algorithms to solve a variety of practical problems on such a family of intervals have been proposed in the literature. Computational tools are developed, and it is shown how they can be used for the purpose of devising cost-optimal parallel algorithms for a number of interval-related problems including finding a largest subset of pairwise nonoverlapping intervals, a minimum dominating subset of intervals, along with algorithms to compute the shortest path between a pair of intervals and, based on the shortest path, a parallel algorithm to find the center of the family of intervals. More precisely, with an arbitrary family of n intervals as input, all algorithms run in O(log n) time using O(n) processors in the EREW-PRAM model of computation.

Olariu, Stephan↗

Algorithms for real-time fault detection of the Space Shuttle Main Engine

This paper reports on the results of a program to develop and demonstrate concepts related to a realtime health management system (HMS) for the Space Shuttle Main Engine (SSME). An HMS framework was developed on the basis of a top-down analysis of the current rocket engine failure modes and the engine monitoring requirements. One result of Phase I of this program was the identification of algorithmic approaches for detecting failures of the SSME. Three different analytical techniques were developed which demonstrated the capability to detect failures significantly earlier than the existing redlines. Based on promising initial results, Phase II of the program was initiated to further validate and refine the fault detection strategy on a large data base of 140 SSME test firings, and implement the resultant algorithms in real time. The paper begins with an overview of the refined algorithms used to detect failures during SSME start-up and main-stage operation. Results of testing these algorithms on a data base of nominal and off-nominal SSME test firings is discussed. The paper concludes with a discussion of the performance of the algorithms operating on a real-time computer system.

Ruiz, C. A.↗