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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 163 records · Page 9

A model for the acoustic impedance of a perforated plate liner with multiple frequency excitation

A nonlinear resistance model is used in the one-dimensional equations of motion with an arbitrary exciting pressure function. The effects of high amplitude fluid motion, grazing flow, and spectral excitation can be studied together. Sample calculations of acoustic resistances are presented using a high amplitude discrete tone superimposed upon a simulated white noise spectrum. The tone amplitude is varied and its effect is shown both with and without a grazing flow velocity.

Rice, E. J.↗

On a stochastic control method for weakly coupled linear systems

The stochastic control of two weakly coupled linear systems with different controllers is considered. Each controller only makes measurements about his own system; no information about the other system is assumed to be available. Based on the noisy measurements, the controllers are to generate independently suitable control policies which minimize a quadratic cost functional. To account for the effects of weak coupling directly, an approximate model, which involves replacing the influence of one system on the other by a white noise process is proposed. Simple suboptimal control problem for calculating the covariances of these noises is solved using the matrix minimum principle. The overall system performance based on this scheme is analyzed as a function of the degree of intersystem coupling.

Kwong, R. H.↗

A model for the acoustic impedance of a perforated plate liner with multiple frequency excitation.

An analytical model for the determination of the acoustic impedance of a perforated plate liner is presented. The model allows the calculation of the effect on acoustic impedance of multiple frequency excitation. A nonlinear resistance model is used in the one-dimensional equations of motion with an arbitrary exciting pressure function. The effects of high amplitude fluid motion, grazing flow, and spectral excitation can thus be studied together. Sample calculations of acoustic resistances are presented using a high amplitude discrete tone superimposed upon a simulated white noise spectrum. The tone amplitude is varied and its effect is shown both with and without a grazing flow velocity.

Rice, E. J.↗

Approximate estimation for systems with quantized data.

Estimation of the state of a nonlinear discrete-time system using quantized data is considered. An exact solution for the maximum likelihood estimate is expressed as the solution of a nonlinear two-point boundary-value problem. Approximate recursive solutions for both the maximum likelihood and the conditional-mean estimates are obtained. The results of Monte-Carlo simulations are presented in which the performance of these two algorithms is compared with that of a Kalman filter in which the quantization error is approximated by white noise.-

Clements, K. A.↗

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.↗

Supervisory sampling and control: Sources of suboptimality in a prediction task

A process supervisor is defined as a person who decides when to sample the process input and what values of a control variable to specify in order to maximize (minimize) a given value function of input sampling period, control setting, and process state. Presented experimental data in such a process where the value function is a time-averaged sampling cost plus mean squared difference between input and control variable. The task was unpaced prediction of the output of a second order filter driven by white noise. Experimental results, when compared to the optical strategy, reveal several consistently suboptimal behaviors. One is a tendency not to choose a long prediction interval even though the optimal strategy dictates that one should. Some results are also interpreted in terms of those input parameters according to which each subjects' behavior would have been nearest optimal. Differences of those parameters from actual input parameters served to quantify how subjects' prediction behavior differed from optimal.

Sheridan, T. B.↗

Tides and tsunamis

Although tides and tsunamis are both shallow water waves, it does not follow that they are equally amenable to an observational program using an orbiting altimeter on a satellite. A numerical feasibility investigation using a hypothetical satellite orbit, real tide observations, and sequentially increased levels of white noise has been conducted to study the degradation of the tidal harmonic constants caused by adding noise to the tide data. Tsunami waves, possibly a foot high and one hundred miles long, must be measured in individual orbits, thus requiring high relative resolution.

Zetler, B. D.↗

Stability of uncertain systems

The asymptotic properties of feedback systems are discussed, containing uncertain parameters and subjected to stochastic perturbations. The approach is functional analytic in flavor and thereby avoids the use of Markov techniques and auxiliary Lyapunov functionals characteristic of the existing work in this area. The results are given for the probability distributions of the accessible signals in the system and are proved using the Prohorov theory of the convergence of measures. For general nonlinear systems, a result similar to the small loop-gain theorem of deterministic stability theory is given. Boundedness is a property of the induced distributions of the signals and not the usual notion of boundedness in norm. For the special class of feedback systems formed by the cascade of a white noise, a sector nonlinearity and convolution operator conditions are given to insure the total boundedness of the overall feedback system.

Blankenship, G. L.↗

A nearest neighbors approach to multidimensional filtering.

The concept of nearest neighbor interaction is applied as a basis for data filtering in two-dimensional steady state problems. A steady state process represented by a potential equation with additive white noise is used to illustrate the application of this concept. It is demonstrated that significant dimensionality reductions can be achieved by applying this concept to various linear steady state problems.

Angel, E.↗

Acquisition and analysis of coastal ground-truth data for correlation with ERTS-1 imagery

The author has identified the following significant results. Radiance profiles drawn along cruise tracks have been examined for use in correlating digital radiance levels with ground truth data. Preliminary examination results are encouraging. Adding weighted levels from the 4 MSS bands appears to enhance specular surface reflections while rendering sensor noise white. Comparing each band signature to the added specular signature ought to enhance non-specular effects caused by ocean turbidity. Preliminary examination of radiance profiles and ground truth turbidity measurements revealed substantial correlation.

Anikouchine, W. A.↗

Structural Aspects of System Identification

The problem of identifying linear dynamical systems is studied by considering structural and deterministic properties of linear systems that have an impact on stochastic identification algorithms. In particular considered is parametrization of linear systems so that there is a unique solution and all systems in appropriate class can be represented. It is assumed that a parametrization of system matrices has been established from a priori knowledge of the system, and the question is considered of when the unknown parameters of this system can be identified from input/output observations. It is assumed that the transfer function can be asymptotically identified, and the conditions are derived for the local, global and partial identifiability of the parametrization. Then it is shown that, with the right formulation, identifiability in the presence of feedback can be treated in the same way. Similarly the identifiability of parametrizations of systems driven by unobserved white noise is considered using the results from the theory of spectral factorization.

Glover, Keith↗

Summer institute in biomedical engineering, 1973

Design and development work is reported for an air filter, an infant weight scale, multiple electrode cardiography, a white noise hearing aid, and a tibial torsion correction device.

Deloatch, E. M.↗

The design of a device for hearer and feeler differentiation, part A

A speech modulated white noise device is reported that gives the rhythmic characteristics of a speech signal for intelligible reception by deaf persons. The signal is composed of random amplitudes and frequencies as modulated by the speech envelope characteristics of rhythm and stress. Time intensity parameters of speech are conveyed through the vibro-tactile sensation stimuli.

Creecy, R.↗

Parameter identifiability of linear dynamical systems

It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.

Glover, K.↗

Summer Institute in Biomedical Engineering, 1973

Bioengineering of medical equipment is detailed. Equipment described includes: an environmental control system for a surgical suite; surface potential mapping for an electrode system; the use of speech-modulated-white-noise to differentiate hearers and feelers among the profoundly deaf; the design of an automatic weight scale for an isolette; and an internal tibial torsion correction study. Graphs and charts are included with design specifications of this equipment.

Deloatch, E. M.↗

Random vibrations of quadratic damping systems

An oscillating system with quadratic damping subjected to white noise excitation is replaced by a nonlinear, statistically equivalent system for which the associated Fokker-Planck equation can be exactly solved. The mean square responses are calculated and the optimum damping coefficient is determined with respect to the minimum mean square acceleration criteria. An application of these results to the optimization of automobile suspension damping is given.

Sireteanu, T.↗

On the identifiability of linear dynamical systems

Consider the situation in which the unknown parameters of a stationary linear system may be parametrized by a set of unknown parameters. The question thus arises of when such a set of parameters can be uniquely identified on the basis of observed data. This problem is considered here both in the case of input and output observations and in the case of output observations in the presence of a white noise input. Conditions for local identifiability are derived for both situations and a sufficient condition for global identifiability is given for the former situation, i.e., when simultaneous input and output observations are available.

Glover, K.↗