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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

Nonparametric Bayer-risk estimation

Nonparametric Bayes risk estimation for measurement classification, using nearest neighbor error rate and Parzen probability density function estimators

Fralick, S. C.↗
NASA NTRS1975

A sequential nonparametric pattern classification algorithm based on the Wald SPRT

A sequential nonparametric pattern classification procedure is presented. The method presented is an estimated version of the Wald sequential probability ratio test (SPRT). This method utilizes density function estimates, and the density estimate used is discussed, including a proof of convergence in probability of the estimate to the true density function. The classification procedure proposed makes use of the theory of order statistics, and estimates of the probabilities of misclassification are given. The procedure was tested on discriminating between two classes of Gaussian samples and on discriminating between two kinds of electroencephalogram (EEG) responses.

Poage, J. L.↗
NASA NTRS1981

A nonparametric identification method for a class of non-linear systems

A relatively simple nonparametric method for the identification of a class of close-coupled nonlinear multi-degree-of-freedom systems has been developed. The identification of arbitrary memoryless nonlinearities is possible through knowledge of the accelerations, velocities, and displacements of the various masses. These quantities are used to obtain the surfaces of the restoring forces as functions of the intermass displacements and velocities. The method was demonstrated by application to a four-degree-of-freedom system to identify the restoring forces. It is found that the identification results are relatively insensitive to measurement noise.

Udwadia, F. E.↗
NASA NTRS1981

Nonparametric identification of a class of nonlinear close-coupled dynamic systems

A nonparametric identification technique for the identification of close coupled dynamic systems with arbitrary memoryless nonlinearities is presented. The method utilizes noisy recorded data (acceleration, velocity and displacement) to identify the restoring forces in the system. The masses in the system are assumed to be known (or fairly well estimated from the design drawings). The restoring forces are expanded in a series of orthogonal polnomials and the coefficients of these polynomial expansions are obtained by using least square fit method. A particularly simple and computationally efficient method is proposed for dealing with separable restoring forces. The identified results are found to be relatively insensitive to measurement noise. An analysis of the effects of measurement noise on the quality of the estimates is given. The computations are shown to be relatively quick (when compared say to the Wiener identification method) and the core storage required relatively small, making the method suitable for onboard identification of large space structures.

Udwadia, F. E.↗
NASA NTRS1984

Parametric and Nonparametric Analysis of LANDSAT TM and MSS Imagery for Detecting Submerged Plant Communities

The spatial, spectral and radiometric characteristics of LANDSAT TM and MSS imagery for detecting submerged aquatic vegetation are assessed. The problem is approached from two perspectives; purely stochastic or nonparametric in a radiative sense and theoretical in which radiative transfer equations are used to predict upwelling radiance at satellite altitude. The spectral and radiometric aspects of the theoretical approach are addressed with which a submerged plant canopy is distinguished from a surrounding bottom of sand or mud.

Ackleson, S. G.↗
NASA NTRS1985

Nonparametric solutions to the variational principle of ideal magnetohydrodynamics

In an effort to gain a better understanding of MHD equilibria in three dimensions, the lower dimensional cases are studied. The solution of the three-dimensional problem is based on the classical variational principle of ideal magnetohydrodynamics. The crucial assumption for the numerical method is the existence of a nested set of toroidal flux surfaces, which is then used as a coordinate. This paper studies the nonparametric solutions to this variational problem in those cases when the direct solution is known to have islands. A form of the variational principle for the slab geometry is described; the one-dimensional problem is analyzed; and asymptotic expansions and numerical solutions to the two-dimensional problem are discussed. An example is presented which shows that the assumption of nested flux surfaces need not rule out the occurrence of islands.

Betancourt, O. L.↗