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At least 667 records · Page 37
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NASA NTRS1989

Population studies in groups and clusters of galaxies. II - A catalog of galaxies in the central 3.5 deg of the Fornax Cluster

A catalog of 2678 galaxies within an area of about 40 sq deg centered on the Fornax Cluster has been compiled based on 26 deep large-scale plates obtained with the 2.5-m Las Campanas Observatory reflector. The catalog includes 340 likely cluster members and 2338 likely background galaxies. Radial velocities are given for 89 of the galaxies. The spatial distributions of various types of galaxies have been modeled as the sum of a King (1962) model cluster component superimposed on a uniform background. Using maximum-likelihood fits to these distributions, a core radius of 0.7 deg is found for a King model fit to the cluster, suggesting that there are few cluster members contained in the sample of background galaxies.

Ferguson, Henry C.↗
NASA NTRS1989

Frequency estimation techniques for high dynamic trajectories

A comparison is presented of four different estimation techniques applied to the problem of continuously estimating the rapidly varying parameters of a sinusoidal signal, observed in the presence of additive noise. Frequency estimates are emphasized, although phase and/or frequency rate are also estimated by some of the algorithms. These parameters are related to the velocity, position, and acceleration of the maneuvering receiver or transmitter. Estimated performance at low carrier-to-noise ratios and high dynamics is investigated for the purpose of determining the useful operating range of an approximate maximum-likelihood estimator, an extended Kalman filter, a cross-product automatic frequency loop, and a phase-locked loop. Numerical simulations are used to evaluate performance while tracking a common trajectory exhibiting high dynamics.

Vilnrotter, Victor A.↗
NASA NTRS1989

A multilevel approach to the design of dc-free line codes

A multilevel approach to the design of dc-free line codes is presented. The different levels can be used for different purposes; for example, to control the maximum accumulated charge or to guarantee a certain minimum distance. The advantages of codes designed by this method over similar codes are the improved run-length/accumulated-charge parameters, higher transmission rate, and the systematic nature of the code construction. The multilevel structure allows the redundancy in the signal selection procedure to be allocated efficiently among the different levels. It also allows the use of suboptimal staged decoding procedures that have performance/complexity advantages over maximum-likelihood decoding.

Calderbank, A. R.↗
NASA NTRS1989

Classification of merged AVHRR and SMMR Arctic data with neural networks

A forward-feed back-propagation neural network is used to classify merged AVHRR and SMMR summer Arctic data. Four surface and eight cloud classes are identified. Partial memberships of each pixel to each class are examined for spectral ambiguities. Classification results are compared to manual interpretations and to those determined by a supervised maximum likelihood procedure. Results indicate that a neural network approach offers advantages in ease of use, interpretability, and utility for indistinct and time-variant spectral classes.

Key, J.↗
NASA NTRS1989

Identification of Space Shuttle Main Engine dynamics

System identification techniques are used to represent the dynamic behavior of the Space Shuttle Main Engine. The transfer function matrices of the linearized models of both the closed loop and the open loop system are obtained by using the recursive maximum likelihood method.

Duyar, Ahmet↗
NASA NTRS1989

Multi-level bandwidth efficient block modulation codes

The multilevel technique is investigated for combining block coding and modulation. There are four parts. In the first part, a formulation is presented for signal sets on which modulation codes are to be constructed. Distance measures on a signal set are defined and their properties are developed. In the second part, a general formulation is presented for multilevel modulation codes in terms of component codes with appropriate Euclidean distances. The distance properties, Euclidean weight distribution and linear structure of multilevel modulation codes are investigated. In the third part, several specific methods for constructing multilevel block modulation codes with interdependency among component codes are proposed. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C which has the same rate as C, a minimum squared Euclidean distance not less than that of code C, a trellis diagram with the same number of states as that of C and a smaller number of nearest neighbor codewords than that of C. In the last part, error performance of block modulation codes is analyzed for an AWGN channel based on soft-decision maximum likelihood decoding. Error probabilities of some specific codes are evaluated based on their Euclidean weight distributions and simulation results.

Lin, Shu↗
NASA NTRS1989

Multiple symbol differential detection of uncoded and trellis coded MPSK

A differential detection for MPSK, which uses a multiple symbol observation interval, is presented and its performance analyzed and simulated. The technique makes use of maximum-likelihood sequence estimation of the transmitted phases rather than symbol-by-symbol detection as in conventional differential detection. As such the performance of this multiple symbol detection scheme fills the gap between conventional (two-symbol observation) differentially coherent detection of MPSK and ideal coherent of MPSK with differential encoding. The amount of improvement gained over conventional differential detection depends on the number of phases, M, and the number of additional symbol intervals added to the observation. What is particularly interesting is that substantial performance improvement can be obtained for only one or two additional symbol intervals of observation. The analysis and simulation results presented are for uncoded and trellis coded MPSK.

Divsalar, Dariush↗
NASA NTRS1990

Estimation in a discrete tail rate family of recapture sampling models

In the context of recapture sampling design for debugging experiments the problem of estimating the error or hitting rate of the faults remaining in a system is considered. Moment estimators are derived for a family of models in which the rate parameters are assumed proportional to the tail probabilities of a discrete distribution on the positive integers. The estimators are shown to be asymptotically normal and fully efficient. Their fixed sample properties are compared, through simulation, with those of the conditional maximum likelihood estimators.

Gupta, Rajan↗
NASA NTRS1990

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Smith, William L.↗
NASA NTRS1990

More data on (possible) gamma ray (point) sources

The 2CG catalog of gamma ray sources was compiled before detailed knowledge was available on the fine-scale structure of the diffuse Galactic gamma-ray emission. Two independent analyses to discriminate sources which are either compact objects of due to very local and strong enhancements in the Galactic cosmic-ray distribution from those which are artifacts due to the clumpy gas distribution are about to be completed: a maximum likelihood analysis and a cross correlation analysis. Arguments are given why differences, and therefore confusion, and in resulting source lists can be expected. Detailed analysis of all COS-B gamma-ray data on Geminga (2CG195+04), reveals the existence of a drastic spectral break below 200 MeV. A power-law spectrum with index -1.88 fits the data above about 100 MeV to 3.2 GeV, however, there are also indications for a spectral break above these energies. For energies above about 100 MeV no evidence for a long-term time variability was found. The error region of Geminga was searched for a radio counterpart at wavelengths of 90, 49, 21, 6, and 2 cm using the Westerbork Synthesis Radio Telescope and the Very Large Array. So far, 16 sources were detected in this error region. In the direction of 1E0630+178, the Einstein x ray source proposed to be a Vela-like pulsar and the counterpart of Geminga, no radio source was found at 21, 49, and 90 cm with 3 sigma upper limits on the flux densities ranging from 0.5 mJy at 21 cm to 4.5 mJy at 90 cm. Detailed structures in local molecular cloud complexes are so far only resolved in gamma rays for the closet and most massive complexes, namely those in the Orion-Monoceros and the Ophiuchus regions. For both region, there is circumstantial evidence for gamma ray emission from molecular gas that was photodissociated after the passage of a SN shell.

Hermsen, W.↗
NASA NTRS1990

Design of ceramic components with the NASA/CARES computer program

The ceramics analysis and reliability evaluation of structures (CARES) computer program is described. The primary function of the code is to calculate the fast-fracture reliability or failure probability of macro-scopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. CARES uses results from MSC/NASTRAN or ANSYS finite-element analysis programs to evaluate how inherent surface and/or volume type flaws component reliability. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effects of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or uniform uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for a single or multiple failure modes by using a least-squares analysis or a maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-to-fit-tests, 90 percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan 90 percent confidence band values are also provided. Examples are provided to illustrate the various features of CARES.

Nemeth, Noel N.↗
NASA NTRS1990

A hybrid M-algorithm/sequential decoder for convolutional and trellis codes

The Viterbi Algorithm (VA) is optimum in the sense of being maximum likelihood for decoding codes with a trellis structure. However, since the VA is in fact an exhaustive search of the code trellis, the complexity of the VA grows exponentially with the constraint length upsilon. This limits its application to codes with small values of upsilon and relatively modest coding gains. The M-Algorithm (MA) is a limited search scheme which carries forward M paths in the trellis, all of the same length. All successors of the M paths are extended at the next trellis depth, and all but the best M of these are dropped. Since a limited search convolutional decoder will flounder indefinitely if one of the paths in storage is not the correct one, the data are usually transmitted in blocks. It has been shown that the performance of the MA approaches the VA at high signal to noise ratios (SNR's) with an M which is far less than the 2 sup upsilon states in the full trellis. Thus the MA can be used with larger values of upsilon, making larger coding gains possible at high SNR's. However, it still requires a relatively large fixed computational effort to achieve good performance.

Wang, Fu-Quan↗
NASA NTRS1990

Ceramics Analysis and Reliability Evaluation of Structures (CARES). Users and programmers manual

This manual describes how to use the Ceramics Analysis and Reliability Evaluation of Structures (CARES) computer program. The primary function of the code is to calculate the fast fracture reliability or failure probability of macroscopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. The program uses results from MSC/NASTRAN or ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effect of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or unifrom uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for single or multiple failure modes by using the least-square analysis or the maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-of-fit tests, ninety percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan ninety percent confidence band values are also provided. The probabilistic fast-fracture theories used in CARES, along with the input and output for CARES, are described. Example problems to demonstrate various feature of the program are also included. This manual describes the MSC/NASTRAN version of the CARES program.

Nemeth, Noel N.↗
NASA NTRS1990

A method of classification for multisource data in remote sensing based on interval-valued probabilities

An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.

Kim, Hakil↗
NASA NTRS1989

The computation of generalized cross-validation functions through householder tridiagonalization with applications to the fitting of interaction spline models

An efficient algorithm for computing the generalized cross-validation function for the general cross-validated regularization/smoothing problem is provided. This algorithm is appropriate for problems where no natural structure is available, and the regularization/smoothing problem is solved (exactly) in a reproducing kernel Hilbert space. It is particularly appropriate for certain multivariate smoothing problems with irregularly spaced data, and certain remote sensing problems, such as those that occur in meteorology, where the sensors are arranged irregularly. The algorithm is applied to the fitting of interaction spline models with irregularly spaced data and two smoothing parameters; favorable timing results are presented. The algorithm may be extended to the computation of certain generalized maximum likelihood (GML) functions. Application of the GML algorithm to a problem in numerical weather forecasting, and to a broad class of hypothesis testing problems, is noted.

Gu, Chong↗
NASA NTRS1989

Cloud identification for ERBE radiative flux retrieval

A maximum likelihood estimation (MLE) technique to the problem of cloud identification using coarse resolution broadband satellite data is developed and tested using simulated satellite observations. The results suggest that, in the determination of cloud conditions for the inversion of satellite-measured radiances to fluxes, the MLE method is an improvement over a Lambertian earth assumption and the clear/cloud threshold used in the inversion of Nimbus 3 and Nimbus 7 data. The use of the MLE method in the operational processing of Earth Radiation Budget Experiment scanner data is considered.

Wielicki, Bruce A.↗
NASA NTRS1990

X-ray studies of coeval star samples. II - The Pleiades cluster as observed with the Einstein Observatory

Coronal X-ray emission of the Pleiades stars is investigated, and maximum likelihood, integral X-ray luminosity functions are computed for Pleiades members in selected color-index ranges. A detailed search is conducted for long-term variability in the X-ray emission of those stars observed more than once. An overall comparison of the survey results with those of previous surveys confirms the ubiquity of X-ray emission in the Pleiades cluster stars and its higher rate of emission with respect to older stars. It is found that the X-ray emission from dA and early dF stars cannot be proven to be dissimilar to that of Hyades and field stars of the same spectral type. The Pleiades cluster members show a real rise of the X-ray luminosity from dA stars to early dF stars. X-ray emission for the young, solarlike Pleiades stars is about two orders of magnitude more intense than for the nearby solarlike stars.

Micela, G.↗
NASA NTRS1989

Cloud classification from satellite data using a fuzzy sets algorithm - A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗