Results 1 to 10 of about 146,305 (262)
Some of the next articles are maybe not open access.
Harmonic retrieval in colored non-Gaussian noise
1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999This paper addresses the harmonic retrieval problem in colored linear non-Gaussian noise of unknown covariance and unknown distribution. The assumptions made in the reported studies, that the non-Gaussian noise is asymmetrically distributed and no quadratic phase coupling occurs, are released. Using the elaborately defined fourth-order cumulants of the
Yan Zhang, Shuxun Wang
openaire +1 more source
Arrival angle estimation in non-Gaussian noise
Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002This paper considers the problem of estimating the direction of arrival of plane waves from sensor array data. It is shown through a multivariate generalization of Whittle's inequality that the least squares estimator and its subspace-based approximations are inefficient when the noise distribution is non-Gaussian.
Debasis Sengupta, Sarbani Palit
openaire +1 more source
Control for nonlinear system with non-Gaussian noise
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017In this paper, a new nonlinear loop transfer recovery control method is proposed for nonlinear systems with non-Gaussian noise. For the proposed control scheme, a dynamical feedback and an optimized cubature Kalamn filter is combined. With such method, it is shown that the deviation of the set point and the system's output could be amended by the ...
Shuang Zhang, Juan Chen, Yakun Yu
openaire +1 more source
Detection of weak signals in non-Gaussian noise
IEEE Transactions on Information Theory, 1981A locally optimum detector structure is derived for the detection of weak signals in non-Gaussian environments. Optimum performance is obtained by employing a zero-memory nonlinearity prior to the matched filter that would be optimum for detecting the signal were the noise Gaussian.
Ning Hsing Lu, Bruce A. Eisenstein
openaire +2 more sources
Polarimetric adaptive detection in non-Gaussian noise
Signal Processing, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Antonio De Maio, Giuseppa Alfano
openaire +3 more sources
Adaptive Filtering of Non-Gaussian Flicker Noise
2020 9th Mediterranean Conference on Embedded Computing (MECO), 2020The article deals with ultra-low-power signals and methods of its receiving and processing in the information transmission systems applied to the systems of the Internet of things (IoT). High requirements for energy efficiency in IoT systems and a low information transmission rate leads to implementation of ultra-narrow band signals, which may be ...
Alexander Parshin, Yuri Parshin
openaire +1 more source
Vibration with Non-Gaussian Noise
Journal of the IEST, 2009Three methods are introduced for generating realizations of time histories with a specified auto-spectral density while controlling the kurtosis. One of the methods also allows the skewness to be specified. A second method allows large excursions (that produce large kurtosis) to be randomly distributed or almost periodic. In addition, the second method
openaire +1 more source
DETECTION OF NON-GAUSSIAN PROCESSES IN NON GAUSSIAN NOISE
1963Abstract : The detection of stochastic processes in noise is considered, under the assumption that neither the signal nor the noise need be Gaussian. The detector structure is found in terms of the semiinvariants of the signal and noise processes. The general detector structure is extremely complicated, but a threshold form may be obtained.
openaire +1 more source
Neural detectors for signals in non-Gaussian noise
IEEE International Conference on Acoustics Speech and Signal Processing, 1993The authors demonstrate that a neural network can be trained for the purpose of detecting a known signal corrupted by additive Gaussian as well as non-Gaussian noise of the impulse type. It is shown that, in the presence of Gaussian noise, the performance of a properly trained neural network is very similar to that of the optimum matched filter ...
Viswanath Ramamurti +2 more
openaire +2 more sources
On non-Gaussian innovations processes for observations with non-Gaussian noise
1986 25th IEEE Conference on Decision and Control, 1986It is well-known that for observations with additive Gaussian noise, the innovations process is a Brownian motion process which, under certain conditions, has the same information as the observation. In this paper, it is shown that for observations with non-Gaussian noise, a Brownian motion process cannot be informationally equivalent to the ...
openaire +1 more source