The use of Gaussian functions in radio astronomy source measurements
Gaussian distribution analysis of radio source observation
Cogdell, J. R.↗
SEARCH · Engineering Papers
Results for “gaussian”
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Predicting PLL threshold behavior with sinusoidal and Gaussian modulation using the Rice-Ridgeway criteria
Signal to noise threshold behavior for sinusoidal and Gaussian modulation using Rice-Ridgeway criteria
Loch, F. J.↗
Ideal limiting of digital signals in Gaussian noise
Output autocorrelation properties of ideal limiters driven by binary deterministic signal plus stationary zero-mean Gaussian noise
Painter, J. H.↗
A review of some results on the design of signals for Gaussian noise and intersymbol interference immunity
Signal design for Gaussian noise and intersymbol interference immunity, discussing bandlimited signals and maximum likelihood detection technique
Simon, M. K.↗
Rate distortion function for a Gaussian source model of images
Gaussian source model of image, deriving rate distortion function under mean square error criterion
Habibi, A.↗
Gaussian feedback communication systems with weak noise in the feedback link
Coding for feedback communication system with additive white Gaussian noise, using mean-square estimation error
Sworder, D. D.↗
Detection, estimation, and modulation theory, Part 3 - Radar-sonar signal processing and Gaussian signals in noise
Book on detection, estimation and modulation theory, Part 3, Gaussian and radar-sonar signals in noise, covering point targets, random process and scatter channels
Van Trees, H. L.↗
Simulation of flight maneuver-load distributions by utilizing stationary, non-Gaussian random load histories
Random numbers were generated with the aid of a digital computer and transformed such that the probability density function of a discrete random load history composed of these random numbers had one of the following non-Gaussian distributions: Poisson, binomial, log-normal, Weibull, and exponential. The resulting random load histories were analyzed to determine their peak statistics and were compared with cumulative peak maneuver-load distributions for fighter and transport aircraft in flight.
Leybold, H. A.↗
A wideband Gaussian noise generator utilizing simultaneously generated pn-sequences.
A digital system has been constructed for the generation of wideband Gaussian noise with a spectrum which is flat to within plus or minus 0.5 dB from 0 to 10 MHz. These characteristics are substantially better than those of commercially available analog noise generators, and are required in testing and simulation of wideband communications systems. The noise is generated by the analog summation of thirty essentially independent binary waveforms, clocked at 35 MHz, and low-pass filtered to 10 MHz.
Hurd, W. J.↗
Recursive ideal observer detection of known M-ary signals in multiplicative and additive Gaussian noise.
This paper presents the derivation of the recursive algorithms necessary for real-time digital detection of M-ary known signals that are subject to independent multiplicative and additive Gaussian noises. The motivating application is minimum probability of error detection of digital data-link messages aboard civil aircraft in the earth reflection multipath environment. For each known signal, the detector contains one Kalman filter and one probability computer. The filters estimate the multipath disturbance. The estimates and the received signal drive the probability computers. Outputs of all the computers are compared in amplitude to give the signal decision. The practicality and usefulness of the detector are extensively discussed.
Painter, J. H.↗
Development and application of a non-Gaussian atmospheric turbulence model for use in flight simulators
A method is described for generating time histories which model the frequency content and certain non-Gaussian probability characteristics of atmospheric turbulence including the large gusts and patchy nature of turbulence. Methods for time histories using either analog or digital computation are described. A STOL airplane was programmed into a 6-degree-of-freedom flight simulator, and turbulence time histories from several atmospheric turbulence models were introduced. The pilots' reactions are described.
Reeves, P. M.↗
An all digital phase locked loop for synchronization of a sinusoidal signal embedded in white Gaussian noise
An all digital phase locked loop which tracks the phase of the incoming sinusoidal signal once per carrier cycle is proposed. The different elements and their functions and the phase lock operation are explained in detail. The nonlinear difference equations which govern the operation of the digital loop when the incoming signal is embedded in white Gaussian noise are derived, and a suitable model is specified. The performance of the digital loop is considered for the synchronization of a sinusoidal signal. For this, the noise term is suitably modelled which allows specification of the output probabilities for the two level quantizer in the loop at any given phase error. The loop filter considered increases the probability of proper phase correction. The phase error states in modulo two-pi forms a finite state Markov chain which enables the calculation of steady state probabilities, RMS phase error, transient response and mean time for cycle skipping.
Reddy, C. P.↗
Tree encoding of Gaussian sources
Tree codes are known to be capable of performing arbitrarily close to the rate-distortion function for any memoryless source and single-letter fidelity criterion. Tree coding and tree search strategies are investigated for the discrete-time memoryless Gaussian source encoded for a signal-power-to-mean-squared-error ratio of about 30 dB (about 5 binary digits per source output). Also, a theoretical lower bound on average search effort is derived. Two code search strategies (the Viterbi algorithm and the stack algorithm) were simulated in assembly language on a large digital computer. After suitable modifications, both strategies yielded encoding with a signal-to-distortion ratio about 1 dB below the limit set by the rate-distortion function. Although this performance is better than that of any previously known instrumentable scheme, it unfortunately requires search computation of the order of 100,000 machine cycles per source output encoded.
Dick, R. J.↗
Weighted adaptive algorithms for estimation of Gaussian distribution parameters
Two weighted adaptive algorithms are proposed for updating the estimates of the mean vector and the covariance matrix, respectively, in a multispectral pattern recognition system. To achieve computational efficiency, the auxiliary matrices have been utilized in the algorithm for covariance matrix updating. Enhancements in the performance accuracy of a multispectral processing system and extensions of the Gaussian maximum likelihood classification capabilities to larger scale surveys are the motivations in developing the algorithms presented herein.
Chang, C. Y.↗
An empirical analysis of the distribution of the duration of overshoots in a stationary gaussian stochastic process
This analysis utilizes computer simulation and statistical estimation. Realizations of stationary gaussian stochastic processes with selected autocorrelation functions are computer simulated. Analysis of the simulated data revealed that the mean and the variance of a process were functionally dependent upon the autocorrelation parameter and crossing level. Using predicted values for the mean and standard deviation, by the method of moments, the distribution parameters was estimated. Thus, given the autocorrelation parameter, crossing level, mean, and standard deviation of a process, the probability of exceeding the crossing level for a particular length of time was calculated.
Parrish, R. S.↗
Programs for computing abscissas and weights for classical and nonclassical Gaussian quadrature formulas
Computer programs for computing Gaussian quadrature abscissas and weights are described. For the classical case the programs use Laguerre iteration to compute abscissas as zeros of orthogonal polynomials. The polynomials are evaluated from known recursion coefficients. The nonclassical case is handled similarly except that the recursion coefficients are computed by numerical integration. A sample problem, with input and output, is presented to illustrate the use of the programs. It computes the quadrature abscissas and weights associated with the weight function over the interval (0,1) for quadrature orders from 16 to 96 in increments of 8.
Desmarais, R. N.↗
Optimum quantisers for a Gaussian input probability density and for the magnitude-error distortion measure
The parameters of non-uniform and uniform quantizers up to ten bits of quantization, optimum for a Gaussian input probability and for the magnitude-error distortion criterion are computed. Optimum quantizers must be understood as quantizers with minimum distortion. The numerical method used for the optimization converges relatively rapidly. The comparison between optimum non-uniform quantizers and optimum uniform quantizers is made.
Demaret, J. C.↗
An algorithm for optimal single linear feature extraction from several Gaussian pattern classes
A computational algorithm is presented for the extraction of an optimal single linear feature from several Gaussian pattern classes. The algorithm minimizes the increase in the probability of misclassification in the transformed (feature) space. Numerical results on the application of this procedure to the remotely sensed data from the Purdue Cl flight line as well as LANDSAT data are presented. It was found that classification using the optimal single linear feature yielded a value for the probability of misclassification on the order of 30% less than that obtained by using the best single untransformed feature. Also, the optimal single linear feature gave performance results comparable to those obtained by using the two features which maximized the average divergence.
Starks, S. A.↗