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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 19 records

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NASA NTRS1980

Alternate symbol inversion for improved symbol synchronization in convolutionally coded systems

Inverting alternate symbols of the encoder output of a convolutionally coded system provides sufficient density of symbol transitions to guarantee adequate symbol synchronizer performance, a guarantee otherwise lacking. Although alternate symbol inversion may increase or decrease the average transition density, depending on the data source model, it produces a maximum number of contiguous symbols without transition for a particular class of convolutional codes, independent of the data source model. Further, this maximum is sufficiently small to guarantee acceptable symbol synchronizer performance for typical applications. Subsequent inversion of alternate detected symbols permits proper decoding.

Simon, M. K.↗

NASA NTRS1989

Performance of the split-symbol moments SNR estimator in the presence of inter-symbol interference

The Split-Symbol Moments Estimator (SSME) is an algorithm that is designed to estimate symbol signal-to-noise ratio (SNR) in the presence of additive white Gaussian noise (AWGN). The performance of the SSME algorithm in band-limited channels is examined. The effects of the resulting inter-symbol interference (ISI) are quantified. All results obtained are in closed form and can be easily evaluated numerically for performance prediction purposes. Furthermore, they are validated through digital simulations.

Shah, B.↗

NASA NTRS2010

Symbolic PathFinder: Symbolic Execution of Java Bytecode

Symbolic Pathfinder (SPF) combines symbolic execution with model checking and constraint solving for automated test case generation and error detection in Java programs with unspecified inputs. In this tool, programs are executed on symbolic inputs representing multiple concrete inputs. Values of variables are represented as constraints generated from the analysis of Java bytecode. The constraints are solved using off-the shelf solvers to generate test inputs guaranteed to achieve complex coverage criteria. SPF has been used successfully at NASA, in academia, and in industry.

Pasareanu, Corina S.↗

NASA NTRS2007

Noncoherent DTTLs for Symbol Synchronization

Noncoherent data-transition tracking loops (DTTLs) have been proposed for use as symbol synchronizers in digital communication receivers. [Communication- receiver subsystems that can perform their assigned functions in the absence of synchronization with the phases of their carrier signals ( carrier synchronization ) are denoted by the term noncoherent, while receiver subsystems that cannot function without carrier synchronization are said to be coherent. ] The proposal applies, more specifically, to receivers of binary phase-shift-keying (BPSK) signals generated by directly phase-modulating binary non-return-to-zero (NRZ) data streams onto carrier signals having known frequencies but unknown phases. The proposed noncoherent DTTLs would be modified versions of traditional DTTLs, which are coherent. The symbol-synchronization problem is essentially the problem of recovering symbol timing from a received signal. In the traditional, coherent approach to symbol synchronization, it is necessary to establish carrier synchronization in order to recover symbol timing. A traditional DTTL effects an iterative process in which it first generates an estimate of the carrier phase in the absence of symbol-synchronization information, then uses the carrier-phase estimate to obtain an estimate of the symbol-synchronization information, then feeds the symbol-synchronization estimate back to the carrier-phase-estimation subprocess. In a noncoherent symbol-synchronization process, there is no need for carrier synchronization and, hence, no need for iteration between carrier-synchronization and symbol- synchronization subprocesses. The proposed noncoherent symbolsynchronization process is justified theoretically by a mathematical derivation that starts from a maximum a posteriori (MAP) method of estimation of symbol timing utilized in traditional, coherent DTTLs. In that MAP method, one chooses the value of a variable of interest (in this case, the offset in the estimated symbol timing) that causes a likelihood function of symbol estimates over some number of symbol periods to assume a maximum value. In terms that are necessarily oversimplified to fit within the space available for this article, it can be said that the mathematical derivation involves a modified interpretation of the likelihood function that lends itself to noncoherent DTTLs. The proposal encompasses both linear and nonlinear noncoherent DTTLs. The performances of both have been computationally simulated; for comparison, the performances of linear and nonlinear coherent DTTLs have also been computationally simulated. The results of these simulations show that, among other things, the expected mean-square timing errors of coherent and noncoherent DTTLs are relatively insensitive to window width. The results also show that at high signal-to-noise ratios (SNRs), the performances of the noncoherent DTTLs approach those of their coherent counterparts at, while at low SNRs, the noncoherent DTTLs incur penalties of the order of 1.5 to 2 dB.

Simon, Marvin↗

NASA NTRS1994

A comparison of full-spectrum and complex-symbol combining techniques for the Galileo S-band mission

Full-spectrum combining (FSC) and complex-symbol combining (CSC) are two antenna-arraying techniques being considered for the Galileo spacecraft's upcoming encounter with Jupiter. This article describes the performance of these techniques in terms of symbol signal-to-noise ratio (SNR) degradation and symbol SNR loss. It is shown that both degradation and loss are approximately equal at low values of symbol SNR but diverge at high SNR values. For the Galileo S-band (2.2 to 2.3 GHz) mission, degradation provides a good estimate of performance as the symbol SNR is typically below -5 dB. For the following arrays - two 70-m antennas, one 70-m and one 34-m antenna, one 70-m and two 34-m antennas, and one 70-m and three 34-m antennas - it is shown that FSC has less degradation than CSC when the subcarrier and symbol window-loop bandwidth products are above 3.0, 10.0, 8.5, and 8.2 mHz at the symbol rate of 200 sym/sec, and above 1.2, 4.5, 4.0, and 3.5 mHz at a symbol rate of 400 sym/sec, respectively. Moreover, for an array of four 34-m antennas, FSC has less degradation than CSC when the subcarrier and symbol window-loop bandwidth products are above 0.32 mHz at the symbol rate of 50 sym/sec and above 0.8 mHz at the symbol rate of 25 sym/sec.

Million, S.↗

NASA NTRS2009

A Survey of New Trends in Symbolic Execution for Software Testing and Analysis

Symbolic execution is a well-known program analysis technique which represents values of program inputs with symbolic values instead of concrete (initialized) data and executes the program by manipulating program expressions involving the symbolic values. Symbolic execution has been proposed over three decades ago but recently it has found renewed interest in the research community, due in part to the progress in decision procedures, availability of powerful computers and new algorithmic developments. We provide a survey of some of the new research trends in symbolic execution, with particular emphasis on applications to test generation and program analysis. We first describe an approach that handles complex programming constructs such as input data structures, arrays, as well as multi-threading. We follow with a discussion of abstraction techniques that can be used to limit the (possibly infinite) number of symbolic configurations that need to be analyzed for the symbolic execution of looping programs. Furthermore, we describe recent hybrid techniques that combine concrete and symbolic execution to overcome some of the inherent limitations of symbolic execution, such as handling native code or availability of decision procedures for the application domain. Finally, we give a short survey of interesting new applications, such as predictive testing, invariant inference, program repair, analysis of parallel numerical programs and differential symbolic execution.

Pasareanu, Corina S.↗

NASA NTRS1981

Cross-spectrum symbol synchronization

A popular method of symbol synchronization exploits one aspect of generalized harmonic analysis, normally referred to as the cross-spectrum. Utilizing nonlinear techniques, the input symbol energy is effectively concentrated onto multiples of the symbol clock frequency, facilitating application of conventional phase lock synchronization techniques. A general treatment of the cross-spectrum technique is developed and shown to be applicable across a broad class of symbol modulation formats. An important specific symbol synchronization application is then treated, focusing the general development to provide both insight and quantitative measure of the performance impact associated with variation in these key synchronization parameters: symbol modulation format, symbol transition probability, symbol energy to noise density ratio, and symbol rate to filter bandwidth ratio.

Mccallister, R. D.↗

NASA NTRS2018

Systems and Methods for Transmitting Data Using Parallel Decode Capacity Optimized Symbol Constellations

Transmitters are described that use non-uniformly spaced symbol constellations that have increased capacity compared to conventional constellations. In many embodiments, a transmitter includes a coder configured to receive bits and output encoded bits, a mapper configured to map said encoded bits to symbols in a non-uniform symbol constellation selected from a plurality of symbol constellations, and a modulator configured to generate a signal for transmission via the communication channel using symbols generated by the mapper. In a variety of embodiments, wherein the non-uniform symbol constellation comprises a set of non-uniformly spaced constellation points, and the location points in the non-uniform symbol constellation are chosen to optimize parallel decode capacity of the non-uniform symbol constellation subject to at least one optimization constraint. In many embodiments, the non-uniform symbol constellation is a quadrature amplitude modulation constellation or a phase shift keyed constellation.

Barsoum, Maged F.↗

NASA NTRS1993

Application of symbolic and algebraic manipulation software in solving applied mechanics problems

As its name implies, symbolic and algebraic manipulation is an operational tool which not only can retain symbols throughout computations but also can express results in terms of symbols. This report starts with a history of symbolic and algebraic manipulators and a review of the literatures. With the help of selected examples, the capabilities of symbolic and algebraic manipulators are demonstrated. These applications to problems of applied mechanics are then presented. They are the application of automatic formulation to applied mechanics problems, application to a materially nonlinear problem (rigid-plastic ring compression) by finite element method (FEM) and application to plate problems by FEM. The advantages and difficulties, contributions, education, and perspectives of symbolic and algebraic manipulation are discussed. It is well known that there exist some fundamental difficulties in symbolic and algebraic manipulation, such as internal swelling and mathematical limitation. A remedy for these difficulties is proposed, and the three applications mentioned are solved successfully. For example, the closed from solution of stiffness matrix of four-node isoparametrical quadrilateral element for 2-D elasticity problem was not available before. Due to the work presented, the automatic construction of it becomes feasible. In addition, a new advantage of the application of symbolic and algebraic manipulation found is believed to be crucial in improving the efficiency of program execution in the future. This will substantially shorten the response time of a system. It is very significant for certain systems, such as missile and high speed aircraft systems, in which time plays an important role.

Tsai, Wen-Lang↗

NASA NTRS2006

Instruments for Reading Direct-Marked Data-Matrix Symbols

Improved optoelectronic instruments (specially configured digital cameras) for reading direct-marked data-matrix symbols on the surfaces of optically reflective objects (including specularly reflective ones) are undergoing development. Data-matrix symbols are two-dimensional binary patterns that are used, like common bar codes, for automated identification of objects. The first data-matrix symbols were checkerboard-like patterns of black-and-white rectangles, typically existing in the forms of paint, ink, or detachable labels. The major advantage of direct marking (the marks are more durable than are painted or printed symbols or detachable labels) is offset by a major disadvantage (the marks generated by some marking methods do not provide sufficient contrast to be readable by optoelectronic instruments designed to read black-and-white data-matrix symbols). Heretofore, elaborate lighting, lensing, and software schemes have been tried in efforts to solve the contrast problem in direct-mark matrix- symbol readers. In comparison with prior readers based on those schemes, the readers now undergoing development are expected to be more effective while costing less. All of the prior direct-mark matrix-symbol readers are designed to be aimed perpendicularly to marked target surfaces, and they tolerate very little angular offset. However, the reader now undergoing development not only tolerates angular offset but depends on angular offset as a means of obtaining the needed contrast, as described below. The prototype reader (see Figure 1) includes an electronic camera in the form of a charge-coupled-device (CCD) image detector equipped with a telecentric lens. It also includes a source of collimated visible light and a source of collimated infrared light for illuminating a target. The visible and infrared illumination complement each other: the visible illumination is more useful for aiming the reader toward a target, while the infrared illumination is more useful for reading symbols on highly reflective surfaces. By use of beam splitters, the visible and infrared collimated lights are introduced along the optical path of the telecentric lens, so that the target is illuminated and viewed from the same direction.

Schramm, Harry F.↗

NASA NTRS2006

Symbolic Constraint Maintenance Grid

Version 3.1 of Symbolic Constraint Maintenance Grid (SCMG) is a software system that provides a general conceptual framework for utilizing pre-existing programming techniques to perform symbolic transformations of data. SCMG also provides a language (and an associated communication method and protocol) for representing constraints on the original non-symbolic data. SCMG provides a facility for exchanging information between numeric and symbolic components without knowing the details of the components themselves. In essence, it integrates symbolic software tools (for diagnosis, prognosis, and planning) with non-artificial-intelligence software. SCMG executes a process of symbolic summarization and monitoring of continuous time series data that are being abstractly represented as symbolic templates of information exchange. This summarization process enables such symbolic- reasoning computing systems as artificial- intelligence planning systems to evaluate the significance and effects of channels of data more efficiently than would otherwise be possible. As a result of the increased efficiency in representation, reasoning software can monitor more channels and is thus able to perform monitoring and control functions more effectively.

James, Mark↗

NASA NTRS2014

Statistical Symbolic Execution with Informed Sampling

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

Reliability↗

NASA NTRS2005

Noncoherent Symbol Synchronization Techniques

Traditional methods for establishing symbol synchronization (sync) in digital communication receivers assume that carrier sync has already been established, i.e., the problem is addressed at the baseband level assuming that a 'perfect' estimate of carrier phase is available. We refer to this approach as coherent symbol sync. Since, for NRZ signaling, a suppressed carrier sync loop such as an I-Q Costas loop includes integrate-and-dump (I and D) filters in its in-phase (1) and quadrature (Q) arms, the traditional approach is to first track the carrier in the absence of symbol sync information, then feed back the symbol sync estimate to these filters, and then iterate between the two to a desirable operating level In this paper, we revisit the symbol sync problem by examining methods for obtaining such sync in the absence of carrier phase information, i.e., so-called noncoherent symbol sync loops. We compare the performance of these loops with that of a well-known coherent symbol sync loop and examine the conditions under which one is preferable over the other.

digital communications↗

NASA NTRS1983

Symbol synchronization for the TDRSS decoder

Each 8 bits out of the Viterbi decoder correspond to one symbol of the R/S code. Synchronization must be maintained here so that each 8-bit symbol delivered to the R/S decoder corresponds to an 8-bit symbol from the R/S encoder. Lack of synchronization, would cause an error in almost every R/S symbol since even a - 1-bit sync slip shifts every bit in each 8-bit symbol by one position, therby confusing the mapping betweeen 8-bit sequences and symbols. The error correcting capability of the R/S code would be exceeded. Possible ways to correcting this condition include: (1) designing the R/S decoder to recognize the overload and shifting the output sequence of the inner decoder to establish a different sync state; (2) using the characteristics of the inner decoder to establish symbol synchronization for the outer code, with or without a deinterleaver and an interleaver; and (3) modifying the encoder to alternate periodically between two sets of generators.

Costello, D. J., Jr.↗

NASA NTRS1989

Multiple symbol differential detection of uncoded and trellis coded MPSK

A differential detection for MPSK, which uses a multiple symbol observation interval, is presented and its performance analyzed and simulated. The technique makes use of maximum-likelihood sequence estimation of the transmitted phases rather than symbol-by-symbol detection as in conventional differential detection. As such the performance of this multiple symbol detection scheme fills the gap between conventional (two-symbol observation) differentially coherent detection of MPSK and ideal coherent of MPSK with differential encoding. The amount of improvement gained over conventional differential detection depends on the number of phases, M, and the number of additional symbol intervals added to the observation. What is particularly interesting is that substantial performance improvement can be obtained for only one or two additional symbol intervals of observation. The analysis and simulation results presented are for uncoded and trellis coded MPSK.

Divsalar, Dariush↗

NASA NTRS1990

Multiple-symbol differential detection of MPSK

A differential detection technique for MPSK (multiple-phase shift keying), which uses a multiple-symbol observation interval, is presented, and its performance is analyzed and simulated. The technique makes use of maximum-likelihood sequence estimation of the transmitted phases rather than symbol-by-symbol detection as in conventional differential detection. Thus, the performance of this multiple-symbol detection scheme fills the gap between conventional (two-symbol observation) differentially coherent detection of MPSK and ideal coherent of MPSK with differential encoding. The amount of improvement gained over conventional differential detection depends on the number of phases M and the number of additional symbol intervals added to the observation. What is particularly interesting is that substantial performance improvement can be obtained for only one or two additional symbol intervals of observation. The analysis and simulation results presented are for uncoded MPSK.

Divsalar, Dariush↗

NASA NTRS1991

A comparison of Manchester symbol tracking loops for block 5 applications

The linearized tracking errors of three Manchester (biphase coded) symbol tracking loops are compared to determine which is appropriate for Block 5 receiver applications. The first is a nonreturn to zero (NRZ) symbol synchronizer loop operating at twice the symbol rate (NRZ x 2) so that it operates on half symbols. The second near optimally processes the mid-symbol transitions and ignores the between symbol transitions. In the third configuration, the first two approaches are combined as a hybrid to produce the best performance. Although this hybrid loop is the best at low symbol signal to noise ratios (SNRs), it has about the same performance as the NRZ x 2 loop at higher SNRs (greater than 0-dB E sub s/N sub 0). Based on this analysis, it is tentatively recommended that the hybrid loop be implemented for Manchester data in the Block 5 receiver. However, the high data rate case and the hardware implications of each implementation must be understood and analyzed before the hybrid loop is recommended unconditionally.

Holmes, J. K.↗

NASA NTRS2014

Improving Coverage of Test Cases Generated by Symbolic PathFinder for Programs with Loops

Symbolic execution is a program analysis technique that is used for many purposes, one of which is test-case generation. For loop-free programs, this generates a test-set that achieves path coverage. Program loops, however, imply exponential growth of the number of paths in the best case and non-termination in the worst case. In practice, the number of loop unwindings needs to be bounded for analysis. We consider symbolic execution in the context of the tool Symbolic Pathfinder. This tool extends the model-checker Java Pathfinder and relies on its bounded state-space exploration for termination. We present an implementation of k-bounded loop unwinding, which increases the amount of user-control over the symbolic execution of loops. Bounded unwinding can be viewed as a naive way to prune paths through loops. When using symbolic execution for test-case generation, naively pruning paths is likely at the cost of coverage. In order to improve coverage of branches within a loop body, we present a technique that semi-automatically concretizes variables used in a loop. The basic technique is limited and we therefore present annotations to manually steer symbolic execution towards certain branches, as well as ideas on how the technique can be extended to be more widely applicable.

Programs With Loops↗