On the stochastic maximum principle with ''average'' constraints.
Stochastic maximum principle with averaged constraint developed for control problems affected by stochastic process
RANDOM PROCESS↗
SEARCH · Search NASA
Results for “stochastic processes”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Flowgraph techniques for closed systems.
Flowgraph techniques for closed systems, discussing properties, approximation method, topology equation, frequency response, constraints, oscillatory and stochastic processes, etc
HARMONIC OSCILLATOR↗
Nonlinear filtering - The exact dynamical equations satisfied by the conditional mode.
Exact dynamical equation derived for conditional density mode representing stochastic process
DIFFERENTIAL EQUATION↗
Mathematical problems of modeling stochastic nonlinear dynamic systems
Systems analysis logic applied to mathematical modeling of dynamic nonlinear stochastic processes
Mortensen, R. E.↗
Performance of an M-ary orthogonal communication system using stationary stochastic signals.
Optimum receiver performance for M-ary communication system using stationary stochastic processes in presence of white Gaussian noise
Viterbi, A. J.↗
Analytic function models of noise and modulation
Analytic time function models of stochastic processes of noise and modulation
Bayless, J. W.↗
Optimal estimation in the presence of unknown parameters.
Optimal estimation of sampled stochastic process with finite state unknown parameters
Hilborn, C. G., Jr.↗
Optimal estimation in the presence of unknown parameters.
Adaptive optimal estimation of sampled stochastic process with finite state unknown parameters, using separation technique
Hilborn, C. G., Jr.↗
The control of nonlinear stochastic control systems under discounted performance criteria
Control algorithm for optimization of nonlinear stochastic processes with discounted performance criteria
Harris, C. A.↗
Studies of thrust vector control of large space vehicles Final report
Display systems, fluid amplification techniques, stochastic processes, and thrust vector control systems
Boland, J. S., III↗
Differential geometric methods in system theory.
Discussion of certain problems in system theory which have been or might be solved using some basic concepts from differential geometry. The problems considered involve differential equations, controllability, optimal control, qualitative behavior, stochastic processes, and bilinear systems. The main goal is to extend the essentials of linear theory to some nonlinear classes of problems.
Brockett, R. W.↗
An adaptive technique for a redundant-sensor navigation system.
An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.
Chien, T.-T.↗
Reflectance of vegetation, soil, and water
There are no author-identified significant results in this report. This report deals with the selection of the best channels from the 24-channel aircraft data to represent crop and soil conditions. A three-step procedure has been developed that involves using univariate statistics and an F-ratio test to indicate the best 14 channels. From the 14, the 10 best channels are selected by a multivariate stochastic process. The third step involves the pattern recognition procedures developed in the data analysis plan. Indications are that the procedures in use are satsifactory and will extract the desired information from the data.
Wiegand, C. L.↗
Control theory for random systems
A survey is presented of the current knowledge available for designing and predicting the effectiveness of controllers for dynamic systems which can be modeled by ordinary differential equations. A short discussion of feedback control is followed by a description of deterministic controller design and the concept of system state. The need for more realistic disturbance models led to the use of stochastic process concepts, in particular the Gauss-Markov process. A compensator controlled system, with random forcing functions, random errors in the measurements, and random initial conditions, is treated as constituting a Gauss-Markov random process; hence the mean-square behavior of the controlled system is readily predicted. As an example, a compensator is designed for a helicopter to maintain it in hover in a gusty wind over a point on the ground.
Bryson, A. E., Jr.↗
Power spectral density estimation by spline smoothing in the frequency domain
An approach, based on a global averaging procedure, is presented for estimating the power spectrum of a second order stationary zero-mean ergodic stochastic process from a finite length record. This estimate is derived by smoothing, with a cubic smoothing spline, the naive estimate of the spectrum obtained by applying FFT techniques to the raw data. By means of digital computer simulated results, a comparison is made between the features of the present approach and those of more classical techniques of spectral estimation.
Defigueiredo, R. J. P.↗
Power spectral density estimation by spline smoothing in the frequency domain.
An approach, based on a global averaging procedure, is presented for estimating the power spectrum of a second order stationary zero-mean ergodic stochastic process from a finite length record. This estimate is derived by smoothing, with a cubic smoothing spline, the naive estimate of the spectrum obtained by applying Fast Fourier Transform techniques to the raw data. By means of digital computer simulated results, a comparison is made between the features of the present approach and those of more classical techniques of spectral estimation.-
De Figueiredo, R. J. P.↗
Bounding filter - A simple solution to lack of exact a priori statistics.
Wiener and Kalman-Bucy estimation problems assume that models describing the signal and noise stochastic processes are exactly known. When this modeling information, i.e., the signal and noise spectral densities for Wiener filter and the signal and noise dynamic system and disturbing noise representations for Kalman-Bucy filtering, is inexactly known, then the filter's performance is suboptimal and may even exhibit apparent divergence. In this paper a system is designed whereby the actual estimation error covariance is bounded by the covariance calculated by the estimator. Therefore, the estimator obtains a bound on the actual error covariance which is not available, and also prevents its apparent divergence.
Nahi, N. E.↗
Statistical properties of two sine waves in Gaussian noise.
A detailed study is presented of some statistical properties of a stochastic process that consists of the sum of two sine waves of unknown relative phase and a normal process. Since none of the statistics investigated seem to yield a closed-form expression, all the derivations are cast in a form that is particularly suitable for machine computation. Specifically, results are presented for the probability density function (pdf) of the envelope and the instantaneous value, the moments of these distributions, and the relative cumulative density function (cdf).
Esposito, R.↗