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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Signal-to-noise Ratio and Combiner Weight Estimation for Symbol Stream Combining

A method is presented for signal to noise ratio (SNR) and symbol stream combiner weight estimation. The SNR estimator employs absolute value moments as in an earlier method. The main contribution is that a new algorithm is derived for the combiner weight estimator to remove the large bias at low SNRs. The new algorithm is simulated to combine two independent symbol streams at various SNRs. As an example, the combining two symbol streams at SNRs of -1 dB and -7 dB, conbiner weight estimates using 1000 samples for the -1 dB stream and 10,000 samples for the -7 dB stream achieve an output SNR of -0.039 dB, which is just 0.012 dB below the theoretical limit achievable with perfect knowledge of the SNRs.

Vo, Q. D.↗
NASA NTRS1984

Symbol-stream Combiner: Description and Demonstration Plans

A system is described and demonstration plans presented for antenna arraying by symbol stream combining. This system is used to enhance the signal-to-noise ratio of a spacecraft signals by combining the detected symbol streams from two or more receiving stations. Symbol stream combining has both cost and performance advantages over other arraying methods. Demonstrations are planned on Voyager 2 both prior to and during Uranus encounter. Operational use is possible for interagency arraying of non-Deep Space Network stations at Neptune encounter.

Hurd, W. J.↗
NASA NTRS1986

Effects of quantization on symbol stream combining in a convolutionally coded system

Symbol stream combining has been proposed as a method for arraying signals at different antennas. If the received symbol streams are recorded on tape, it is desirable to limit the required storage without significantly affecting the performance. It is shown that 4-bit quantized symbols introduce an E sub b/N sub o penalty of only 0.05 dB.

Pollara, F.↗
NASA NTRS1987

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Expert systems that require access to data bases, complex simulations and real time instrumentation have both symbolic as well as algorithmic computing needs. These needs could both be met using a general computing workstation running both symbolic and algorithmic code, or separate, specialized computers networked together. The later approach was chosen to implement TEXSYS, the thermal expert system, developed to demonstrate the ability of an expert system to autonomously control the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. Integration options are explored and several possible solutions are presented.

Gregg, Hugh↗
NASA NTRS1988

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Expert systems that require access to data bases, complex simulations and real time instrumentation have both symbolic and algorithmic needs. Both of these needs could be met using a general purpose workstation running both symbolic and algorithmic codes, or separate, specialized computers networked together. The later approach was chosen to implement TEXSYS, the thermal expert system, developed by the NASA Ames Research Center in conjunction with the Johnson Space Center to demonstrate the ability of an expert system to autonomously monitor the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. The integration options and several possible solutions are presented.

Gregg, Hugh↗
NASA NTRS1987

Symbolic modeling of flexible manipulators

An algorithm is presented to symbolically derive the full nonlinear dynamic equations of motion of multilink flexible manipulators. Lagrange's assumed modes method is the basis of new algorithm and adapted in a way suitable for symbolic manipulation by digital computers. It is applied to model a two-link flexible arm by means of a commercially available symbolic manipulation program. The advantages of the algorithm and simulation results are discussed.

Cetinkunt, Sabri↗
NASA NTRS1990

Exact closed-form expressions for the performance of the split-symbol moments estimator of signal-to-noise ratio

Previously, the performance of the split-symbol moments estimator (SSME) of signal-to-noise ratio (SNR) has been evaluated by means of approximate expressions for the estimator mean and variance. These are asymptotic formulas in the sense that they become accurate as the number of estimator samples gets large. Here, exact closed-form expressions are obtained for the same quantities. These expressions confirm the accuracy of the previously derived asymptotic results, and, unlike the asymptotic formulas, they are useful even when the number of samples is small. It is also shown that the conventional split-symbol estimator can be trivially scaled to form a signal-to-noise ratio estimator which is precisely unbiased (as long as the estimate is based on more than two split-symbols).

Dolinar, S.↗
NASA NTRS1990

Application of symbolic computations to the constitutive modeling of structural materials

In applications involving elevated temperatures, the derivation of mathematical expressions (constitutive equations) describing the material behavior can be quite time consuming, involved and error-prone. Therefore intelligent application of symbolic systems to faciliate this tedious process can be of significant benefit. Presented here is a problem oriented, self contained symbolic expert system, named SDICE, which is capable of efficiently deriving potential based constitutive models in analytical form. This package, running under DOE MACSYMA, has the following features: (1) potential differentiation (chain rule), (2) tensor computations (utilizing index notation) including both algebraic and calculus; (3) efficient solution of sparse systems of equations; (4) automatic expression substitution and simplification; (5) back substitution of invariant and tensorial relations; (6) the ability to form the Jacobian and Hessian matrix; and (7) a relational data base. Limited aspects of invariant theory were also incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet pre-defined order and simplify expressions so as to limit expression growth. Results are displayed, when applicable, utilizing index notation. SDICE was designed to aid and complement the human constitutive model developer. A number of examples are utilized to illustrate the various features contained within SDICE. It is expected that this symbolic package can and will provide a significant incentive to the development of new constitutive theories.

Arnold, Steven M.↗
NASA NTRS1991

The analysis of control trajectories using symbolic and database computing

The research broadly concerned the symbolic computation, mixed numeric-symbolic computation, and data base computation of trajectories of dynamical systems, especially control systems. It was determined that trees can be used to compute symbolically series which approximate solutions to differential equations.

Grossman, Robert↗
NASA NTRS1992

Use of symbolic computation in robotics education

An application of symbolic computation in robotics education is described. A software package is presented which combines generality, user interaction, and user-friendliness with the systematic usage of symbolic computation and artificial intelligence techniques. The software utilizes MACSYMA, a LISP-based symbolic algebra language, to automatically generate closed-form expressions representing forward and inverse kinematics solutions, the Jacobian transformation matrices, robot pose error-compensation models equations, and Lagrange dynamics formulation for N degree-of-freedom, open chain robotic manipulators. The goal of such a package is to aid faculty and students in the robotics course by removing burdensome tasks of mathematical manipulations. The software package has been successfully tested for its accuracy using commercially available robots.

Vira, Naren↗
NASA NTRS1993

Slew Timer For Symbol Display Generator

Slew-length timer generates delay and, at end of delay, signal indicating end of one of slews of electron beam in cathode-ray-tube display driven by symbol generator. End-of-slew signal constitutes "permission" for symbol generator to begin drawing next symbol segment.

Fisher, Paul A.↗
NASA NTRS1992

Symbolic discrete event system specification

Extending discrete event modeling formalisms to facilitate greater symbol manipulation capabilities is important to further their use in intelligent control and design of high autonomy systems. An extension to the DEVS formalism that facilitates symbolic expression of event times by extending the time base from the real numbers to the field of linear polynomials over the reals is defined. A simulation algorithm is developed to generate the branching trajectories resulting from the underlying nondeterminism. To efficiently manage symbolic constraints, a consistency checking algorithm for linear polynomial constraints based on feasibility checking algorithms borrowed from linear programming has been developed. The extended formalism offers a convenient means to conduct multiple, simultaneous explorations of model behaviors. Examples of application are given with concentration on fault model analysis.

Zeigler, Bernard P.↗
NASA NTRS1994

Multiple-Symbol, Partially Coherent Detection of MPSK

Proposed method of reception of multiple-phase-shift-keyed (MPSK) radio signals involves multiple-symbol, partially coherent detection. Instead of attempting to determine phase of transmitted signal during each symbol period as in coherent detection, receiver acquires signal data during multiple-symbol observation interval, then produces maximum-likelihood-sequence estimate of phases transmitted during interval. Combination of coherent-reception and incoherent-reception decision rules are used.

Simon, Marvin K.↗
NASA NTRS1998

Symbolic Computational Approach to the Marangoni Convection Problem With Soret Diffusion

A recently reported solution for stationary stability of a thermosolutal system with Soret diffusion is re-derived and examined using a symbolic computational package. Symbolic computational languages are well suited for such an analysis and facilitate a pragmatic approach that is adaptable to similar problems. Linearization of the equations, normal mode analysis, and extraction of the final solution are performed in a Mathematica notebook format. An exact solution is obtained for stationary stability in the limit of zero gravity. A closed form expression is also obtained for the location of asymptotes in relevant parameter, (Sm(sub c), Mac(sub c)), space. The stationary stability behavior is conveniently examined within the symbolic language environment. An abbreviated version of the Mathematica notebook is given in the Appendix.

Skarda, J. Raymond↗
NASA NTRS1999

Combining Automated Theorem Provers with Symbolic Algebraic Systems: Position Paper

In contrast to pure mathematical applications where automated theorem provers (ATPs) are quite capable, proof tasks arising form real-world applications from the area of Software Engineering show quite different characteristics: they usually do not only contain much arithmetic (albeit often quite simple one), but they also often contain reasoning about specific structures (e.g. graphics, sets). Thus, an ATP must be capable of performing reasoning together with a fair amount of simplification, calculation and solving. Therefore, powerful simplifiers and other (symbolic and semi-symbolic) algorithms seem to be ideally suited to augment ATPs. In the following we shortly describe two major points of interest in combining SASs (symbolic algebraic systems) with top-down automated theorem provers (here: SETHEO [Let92, GLMS94]).

Schumann, Johann↗
NASA NTRS2003

Practical Formal Verification of Diagnosability of Large Models via Symbolic Model Checking

This document reports on the activities carried out during a four-week visit of Roberto Cavada at the NASA Ames Research Center. The main goal was to test the practical applicability of the framework proposed, where a diagnosability problem is reduced to a Symbolic Model Checking problem. Section 2 contains a brief explanation of major techniques currently used in Symbolic Model Checking, and how these techniques can be tuned in order to obtain good performances when using Model Checking tools. Diagnosability is performed on large and structured models of real plants. Section 3 describes how these plants are modeled, and how models can be simplified to improve the performance of Symbolic Model Checkers. Section 4 reports scalability results. Three test cases are briefly presented, and several parameters and techniques have been applied on those test cases in order to produce comparison tables. Furthermore, comparison between several Model Checkers is reported. Section 5 summarizes the application of diagnosability verification to a real application. Several properties have been tested, and results have been highlighted. Finally, section 6 draws some conclusions, and outlines future lines of research.

Cavada, Roberto↗
NASA NTRS2005

Multiple Layer Identification Label Using Stacked Identification Symbols

An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.

Harry F Schramm↗
NASA NTRS2005

Multiple layer identification label using stacked identification symbols

An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.

Schramm, Harry F.↗