Robust detection using extreme-value theory.
Robust detection of binary signal in additive noise, using extreme value theory /EVT/ to estimate probability density function and system error and threshold
Milstein, L. B.↗
SEARCH · Engineering Papers
Results for “Probability density function”
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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Least-square methods in abstract pattern recognition.
Least square or least mean square approximation methods in abstract pattern recognition, noting unknown probability density function
Meisel, W. S.↗
Non-Gaussian noise Progress report
Probability density functions for quantization noise, continuous wave interference, impulse noise, and atmospheric noise
Tuncer, K. F.↗
Optimum adaptive reception for binary sequences
Optimum adaptive reception for binary sequences, using posteriori probability density function computing device synthesized from correlator, instantaneous nonlinearity and multiplier
Wintz, P. A.↗
The response of hard-limiting bandpass limiters to PM signals
Hard limiting bandpass limiter output signal to noise ratio in PM signal detection calculated using probability density function
Chang, J. C.↗
First-crossing probabilities of the linear oscillator
Random vibration first threshold crossing probability density function for linear oscillator
Crandall, S. H.↗
Fourier and statistical analysis at random waveforms, part D Final project report
Computer programming formulas for frequency and statistical analysis of random waveform signals including Fourier analysis, probability density functions, and autocorrelation
Luckinbill, D. L.↗
Transient solutions of the Fokker-Planck equation for a class of first-order phase- locked loops
Eigenfunction expansions of reduced nonGaussian phase error transition probability density function for first order tracking loop, analyzing spectral properties of Fokker-Planck equation
La Frieda, J. R.↗
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.↗
Lognormality of small-scale structure of turbulence
Small scale turbulence structure in atmospheric boundary layers over open ocean, noting velocity derivatives probability density function lognormality
Chen, W. Y.↗
A dynamic equation for stochastic magnetic field lines in the galaxy
Galactic stochastic magnetic field lines, deriving dynamic equation for probability density function
Jones, F. C.↗
Recognition of crops and soils by spot density measurements of imagery
Computerized techniques and methods were used to conduct preliminary soil and crop identification experiments. The soil identification experiment was conducted by making densitometer measurements on Ektachrome infrared film exposed at 14,000 feet. The density measurements were analyzed by plotting sample probability density functions, two-dimensional scatter plots, and the use of K-class I to determine the complete set of classification results for one, two, three and four features. Due to the presence of nineteen classes, crop identification experiments were more difficult to formulate. Classes of corn, fallow, harvested wheat, roadways, trees and water were classified 75 percent correct.
Nelson, G. D.↗
Simulation of flight maneuver-load distributions by utilizing stationary, non-Gaussian random load histories
Random numbers were generated with the aid of a digital computer and transformed such that the probability density function of a discrete random load history composed of these random numbers had one of the following non-Gaussian distributions: Poisson, binomial, log-normal, Weibull, and exponential. The resulting random load histories were analyzed to determine their peak statistics and were compared with cumulative peak maneuver-load distributions for fighter and transport aircraft in flight.
Leybold, H. A.↗
Distribution of error in least-squares solution of an overdetermined system of linear simultaneous equations
Probability density functions were derived for errors in the evaluation of unknowns by the least squares method in system of nonhomogeneous linear equations. Coefficients of the unknowns were assumed correct and computational precision were also assumed. A vector space was used, with number of dimensions equal to the number of equations. An error vector was defined and assumed to have uniform distribution of orientation throughout the vector space. The density functions are shown to be insensitive to the biasing effects of the source of the system of equations.
Miller, C. D.↗
Two-way coherent tracking systems.
Review of some results pertinent to the development of nonlinear theory on two-way coherent tracking systems. In particular, the model of cascaded systems is presented, and approximations to steady state probability density functions of the two-way system phase and Doppler error are developed. From these, certain numerical results required in the design and planning of these systems are derived.
Lindsey, W. C.↗
On the probability of cycle-slipping in first-order phase-locked loops.
The first-passage time boundary value problem for first-order phase-locked loops (PLL) is analyzed, and spectral representations are developed for the probability density function (pdf), the distribution function, and the moments of the first time to passage (or cycle-slip). For the sinusoidal PLL, an asymptotic formula, that is surprisingly accurate even at low loop SNR's and large frequency offsets, is obtained for the pdf of the time to cycle-slip, in terms of the mean time to slip.
La Frieda, J. R.↗
Effects of atmospheric irregularities on sonic-boom propagation.
A review is given of information obtained in recent years concerning the effects on sonic-boom signatures of departures of the atmosphere from a perfectly stratified time invariant model. These effects include the observed random variations in boom overpressures from those expected for a stratified atmosphere, the anomalously large and variable rise times, and the occurrence of spiked or rounded waveforms rather than the characteristic N waves. The extent of the variability in data recorded during actual flight tests is summarized in the form of histograms, representing experimentally obtained probability density functions. The physical mechanisms believed to be responsible for the variations and the anomalous features in the signatures are described. These include refraction and subsequent wavefront rippling by turbulence, the possible focusing or defocusing of rays, the formation of caustics, and the phenomenon of wavefront folding, diffraction, and scattering. Recent statistical theories of shock propagation through a turbulent atmosphere proposed by Crow, George and Plotkin, Pierce, Horning, and others are reviewed.
Pierce, A. D.↗
A stochastic model for eye movements during fixation on a stationary target.
A stochastic model describing small eye movements occurring during steady fixation on a stationary target is presented. Based on eye movement data for steady gaze, the model has a hierarchical structure; the principal level represents the random motion of the image point within a local area of fixation, while the higher level mimics the jump processes involved in transitions from one local area to another. Target image motion within a local area is described by a Langevin-like stochastic differential equation taking into consideration the microsaccadic jumps pictured as being due to point processes and the high frequency muscle tremor, represented as a white noise. The transform of the probability density function for local area motion is obtained, leading to explicit expressions for their means and moments. Evaluation of these moments based on the model is comparable with experimental results.
Vasudevan, R.↗