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White noise

About: White noise is a research topic. Over the lifetime, 16496 publications have been published within this topic receiving 318633 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the effect of wind correlation on aircraft conflict probability estimation is examined and the conclusion of the study is that wind correlation may have a significant effect under particular encounter geometries.
Abstract: A study which examines the effect of wind correlation on aircraft conflict probability estimation is presented. We describe the correlation structure of the difference between the actual wind and the meteorological wind forecasts and discuss how it can be implemented in simulation. For several encounters we then examine the aircraft conflict probability estimation errors if the correlation structure is ignored and the wind is instead assumed to be modeled as white noise. The conclusion of the study is that wind correlation may have a significant effect under particular encounter geometries.

79 citations

Journal ArticleDOI
TL;DR: A technique is presented for obtaining bounds on the average probability of error for direct-sequence spread-spectrum multiple-access (DS/SSMA) communications that yields arbitrarily right bounds, involves a small amount of computation, avoids numerical integrations, and applies to many types of detection.
Abstract: A technique is presented for obtaining bounds on the average probability of error for direct-sequence spread-spectrum multiple-access (DS/SSMA) communications. The technique is of interest because it yields arbitrarily right bounds, involves a small amount of computation, avoids numerical integrations, and applies to many types of detection. As an illustration, the technique is applied to binary DS/SSMA communications, an additive white Gaussian noise channel, and a coherent correlation receiver. It is assumed that all the signature sequences are deterministic. Each transmitter is assumed to have the same power, although the approach can accommodate the case of transmitters with unequal powers. Expressions are given for the density functions of the random variables that model the multiple-access interference. These expressions are used to obtain arbitrarily tight upper and lower bounds on the average probability of error without making a Gaussian approximation or performing numerical integrations to incorporate the effects of multiple-access interference. >

79 citations

Journal ArticleDOI
TL;DR: In this paper, a path integral solution for non-linear systems under Poisson white noise is presented, which may be considered as a step-by-step solution technique in terms of probability density function.

79 citations

Journal ArticleDOI
TL;DR: The author investigates the convexity properties of error probability in the detection of binary-valued scalar signals corrupted by additive noise and shows that the error probability of the maximum-likelihood receiver is a convex function of the signal power when the noise has a unimodal distribution.
Abstract: The author investigates the convexity properties of error probability in the detection of binary-valued scalar signals corrupted by additive noise. It is shown that the error probability of the maximum-likelihood receiver is a convex function of the signal power when the noise has a unimodal distribution. Based on this property, the results of the optimal time-sharing strategies of transmitters and jammers, and of the optimal use of multiple channels are obtained.

79 citations

Proceedings ArticleDOI
09 May 1977
TL;DR: In this article, the two-sinusoid frequency resolution of conventional Fourier, autoregressive (AR), and a special ARMA power spectral density (PSD) estimators is considered.
Abstract: The two-sinusoid frequency resolution of conventional Fourier, autoregressive (AR), and a special autoregressive-moving average (ARMA) power spectral density (PSD) estimators is considered in this paper. The conventional Fourier spectrum analysis methods have resolutions which are, on the average, roughly the reciprocal of the observation interval. However, for any particular case of two sinusoids of some initial phases, the resolution may be much greater or much less than the average resolution. The special ARMA PSD estimator can, in principle, perfectly resolve any two sinusoids if the autocorrelation function is perfectly known. The AR spectral estimate has a resolution which varies as a function of signal-to-noise ratio (SNR) from that of the conventional Fourier methods at low SNB to that of the special ARMA method of high SNR. A signal power estimation and a noise power cancellation technique is also presented.

79 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023238
2022535
2021488
2020541
2019558
2018537