Journal ArticleDOI
Detection of weak signals in non-Gaussian noise
Ning Hsing Lu,B. Eisenstein +1 more
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TLDR
The asymptotic detection performance of the locally optimum detector under non-Gaussian conditions is derived and compared with that for the corresponding detector optimized for operations in Gaussian noise.Abstract:
A 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. The asymptotic detection performance of the locally optimum detector under non-Gaussian conditions is derived and compared with that for the corresponding detector optimized for operations in Gaussian noise. Numerical results for the asymptotic detection performance are shown for signal detection in noise environments of practical interest.read more
Citations
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Polynomial Filtering for Linear Discrete Time Non-Gaussian Systems
TL;DR: A new filtering approach for linear discrete time non-Gaussian systems that generalizes a previous result concerning quadratic filtering and will be the mean square optimal one among those estimators that take into account $
u$-polynomials of the last $\Delta$ observations.
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On the use of stochastic resonance in sine detection
TL;DR: This paper recalls some basics of detection and then shows why SR can be used in sine detection context and how to use SR in a detection scheme.
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Optimal linear-quadratic systems for detection and estimation
B. Picinbono,P. Devaut +1 more
TL;DR: It is shown here that the Gaussian assumption can be removed, and a complete solution is presented for an arbitrary probability distribution with finite fourth-order moments.
Journal ArticleDOI
Autocorrelation-Based Spectrum Sensing for Cognitive Radios
Mort Naraghi-Pour,Takeshi Ikuma +1 more
TL;DR: The results show that the proposed algorithm outperforms the covariance detector and the cyclic autocorrelation detector in the presence of noise power uncertainty or in the case of unknown primary signal bandwidth.
Journal ArticleDOI
Locally Optimum and Suboptimum Detector Performance in a Non-Gaussian Interference Environment
TL;DR: One result is that there are situations where the bandpass limiter outperforms the LOBD as the signal level increases; that is, the locally optimum detector may not remain "near optimum" in actual operational situations.