Computation of the pseudinverse of a matrix of unknown rank
Least squares solution to linear system and computation of pseudoinverse by matrix of unknown rank
LEAST SQUARES METHOD↗
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Results for “unknown unknowns”
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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Quantum mechanical study of molecules - Prediction of the ground, ionized and excited states of the unknown NF molecule
Quantum mechanical study of molecules - prediction of ground, ionized, and excited states of unknown nitrogen fluoride molecule
PREDICTION THEORY↗
Acoustic experiment to determine the composition of an unknown planetary atmosphere.
Gaseous composition of unknown planetary atmosphere determined, using acoustic experiment combined with pressure and temperature data
ACOUSTIC IMPEDANCE↗
Optimal adaptive filter realizations for sampled stochastic processes with an unknown parameter
Optimal adaptive filter for sampled stochastic processes with unknown parameter
Hilborn, C. G., Jr.↗
Approximate solutions of M nonlinear equations in N unknowns for M greater than N
Approximate solutions of M nonlinear equations in N unknowns
Greer, C. L.↗
Recursive state estimation - Unknown but bounded errors and system inputs.
State of linear dynamic system using noisy observations with unknown but bounded errors and system inputs, deriving recursive algorithm
Schweppe, F. C.↗
Minimum mean square error approximation of unknown probability distribution functions.
Double stochastic approximation algorithm for minimizing mean square error in finite expansion of unknown probability distribution functions
Deuser, L. M.↗
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 epsilon-capacity of classes of unknown channels.
Unknown channels classes epsilon capacity applied to estimating capacity of channels with additive noise, discussing models and upper and lower bounds
Forys, L. J.↗
Minimax solution of n plus 1 inconsistent linear equations in n unknowns
Algorithm for Chebyshev solution of n plus 1 inconsistent linear equations in n unknowns, using minimax technique
Tewarson, R. P.↗
Investigation of system readiness when some defect types are unknown
Unbiased estimate and tests for readiness index for systems with unknown defects not causing system failure
Huber, E. R.↗
The parameter adaptive control of unknown plants
Application of Liapunov method for parameter adaptive control of unknown plants
Gilbart, J. W.↗
Application of gradient search procedures for the identification of unknown system parameters from system response observations
Gradient search procedures application for nonlinear system unknown parameters identification from system dynamic response observations
Baumgarten, J. R.↗
Analog table look-up device identifies unknown terrain
Table provides a probability map defining unknown terrain in terms of known terrain inputs. Device consists of analog transformation network and flying spot scanner. Information is useful to manufacturers and users of remote sensing equipment and applies to automated quality control.
Dye, R. H.↗
Adaptive control of stochastic linear systems with unknown parameters
The problem of optimal control of linear discrete-time stochastic dynamical system with unknown and, possibly, stochastically varying parameters is considered on the basis of noisy measurements. It is desired to minimize the expected value of a quadratic cost functional. Since the simultaneous estimation of the state and plant parameters is a nonlinear filtering problem, the extended Kalman filter algorithm is used. Several qualitative and asymptotic properties of the open loop feedback optimal control and the enforced separation scheme are discussed. Simulation results via Monte Carlo method show that, in terms of the performance measure, for stable systems the open loop feedback optimal control system is slightly better than the enforced separation scheme, while for unstable systems the latter scheme is far better.
Ku, R. T.↗
An adaptive scheme for observing the state of an unknown linear system
A full order adaptive observer is described for observing the states of a single-input single-output observable continuous differential system with unknown parameters. Convergence of the observer states to those of the system is accomplished by directly changing the parameters of the observer using an adaptive law based upon Liapunov stability theory. Observer eigenvalues may be freely chosen. Some restriction is placed upon the system input in that it must be sufficiently rich in frequencies in order to insure convergence.
Carroll, R. L.↗
Optimal design of an unsupervised adaptive classifier with unknown priors
An adaptive detection scheme for M hypotheses was analyzed. It was assumed that the probability density function under each hypothesis was known, and that the prior probabilities of the M hypotheses were unknown and sequentially estimated. Each observation vector was classified using the current estimate of the prior probabilities. Using a set of nonlinear transformations, and applying stochastic approximation theory, an optimally converging adaptive detection and estimation scheme was designed. The optimality of the scheme lies in the fact that convergence to the true prior probabilities is ensured, and that the asymptotic error variance is minimum, for the class of nonlinear transformations considered. An expression for the asymptotic mean square error variance of the scheme was also obtained.
Kazakos, D.↗