Results 221 to 230 of about 146,305 (262)

Signal interception in non-Gaussian noise

IEEE Transactions on Communications, 1992
The interception of weak signals in nonGaussian noise is discussed. The spectral correlation property exhibited by all cyclostationary signals is exploited to synthesize multi-cycle and single-cycle detectors which assure a superior tolerance (as compared to radiometric techniques) to one of the most challenging problems in interception, namely ...
IZZO, LUCIANO, PAURA, LUIGI, TANDA, MARIO   +2 more
openaire   +2 more sources

Recursive filtering with non-Gaussian noises

IEEE Transactions on Signal Processing, 1996
The Kalman filter is an optimal recursive filter, although its optimality can only be claimed under the Gaussian noise environment. In this paper, we consider the problem of recursive filtering with non-Gaussian noises. One of the most promising schemes, which was proposed by Masreliez (1972, 1975), uses the nonlinear score function as the correction ...
Wen-Rong Wu, Amlan Kundu 0001
openaire   +1 more source

Detection in multivariate non-Gaussian noise

IEEE Transactions on Communications, 1994
The applications of multivariate Edgeworth series and higher-order statistics to the discrete-time detection of a known constant signal in multivariate non-Gaussian noise are considered. A technique to derive suboptimum detectors from the Neyman-Pearson optimum and locally optimum detectors is described.
Benny C. Y. Wong, Ian F. Blake
openaire   +1 more source

Nonlinear Filtering of Non-Gaussian Noise

Journal of Intelligent and Robotic Systems, 1997
This paper introduces a new nonlinear filter for a discrete time, linear system which is observed in additive non-Gaussian measurement noise. The new filter is recursive, computationally efficient and has significantly improved performance over other linear and nonlinear schemes.
Konstantinos N. Plataniotis, Dimitrios Androutsos, Anastasios N. Venetsanopoulos   +2 more
openaire   +1 more source

DETECTING SINUSOIDS IN NON‐GAUSSIAN NOISE

Journal of Time Series Analysis, 1992
Abstract.Spectral analysis is a well‐established procedure for detecting harmonic signals in a noisy environment. Much research has been done on methods that use second‐order statistics (i.e. the autocovariance function and power spectrum) such as Whittle's test, Bartlett's test, Hannan's test and the PriestleyP(Λ) test. When the noise is non‐Gaussian,
Lii, K.-S., Tsou, T.-H.
openaire   +1 more source

Detection of non-Gaussian signals in non-Gaussian noise using the bispectrum

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
The problem of detecting a non-Gaussian time series in the presence of additive Gaussian or non-Gaussian noise is cast into a classical hypothesis testing framework, using the sample bispectrum as the test statistic. The power of the test is demonstrated as a function of signal-to-noise ratio, the degree of skewness of the signal, and processing ...
Melvin J. Hinich, Gary R. Wilson
openaire   +1 more source

Robust Detectors for Signals in Non-Gaussian Noise

IEEE Transactions on Communications, 1977
The robustness of suboptimal nonlinear detectors for known discrete-time signals in non-Gaussian noise is investigated. The measure of robustness used is the degradation of asymptotic relative efficiency (compared to a linear detector) from that achieved by an optimal nonlinear detector.
James H. Miller, John B. Thomas
openaire   +1 more source

Non-Gaussian noise reduction in system identification

Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), 2000
The synergy of signal processing filtering methods and established parameter estimation techniques reduces unwanted effects from noise. Measurement noise, particularly of non-Gaussian type, is known to be problematic in identification and parameter estimation; and a relatively small amount may wreak havoc on linear estimation schemes. Opportunities for
Cheryl B. Schrader, Jack J. Harris
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Local spectrum sensing in non-Gaussian noise

2010 17th International Conference on Telecommunications, 2010
This paper deals with the local spectrum sensing problem in non-Gaussian noise. It is of great importance to reliably detect the presence of licensed users in cognitive radio. This task highly depends on the noise distribution, thus it is important to characterize the noise behavior as best as possible.
Sayed Jalal Zahabi, AliAkbar Tadaion
openaire   +1 more source