Top PDF Adaptive detection of a Gaussian signal in Gaussian noise
Adaptive detection of a Gaussian signal in Gaussian noise
... Department of Electronics, Optronics and Signal 10 Avenue Edouard Belin, 31055 Toulouse France Abstract—Adaptive detection of a Swerling I-II type target in ...
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Adaptive detection of distributed targets in compound-Gaussian noise without secondary data: A Bayesian approach
... Adaptive detection of distributed targets has been addressed in [1] and [2]; noise is modeled in terms of independent, com- plex normal random vectors with a common ...
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Knowledge-aided covariance matrix estimation and adaptive detection in compound-Gaussian noise
... embedded in colored noise modeled in terms of a com- pound-Gaussian ...matrices of the primary and the secondary data share a common structure while having ...
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Generalized Likelihood Ratio Test for Detection of Gaussian Rank-One Signals in Gaussian Noise With Unknown Statistics
... problem of detecting a target in Gaussian noise with unknown covariance ...matrix. In contrast to the usual assumption of deterministic target ampli- tudes, we assume here ...
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On the Optimum Demodulation in the Presence of Gaussian Phase Noise
... one of the foremost solutions to face the exponential growth of the data ...phase noise. This paper addresses the design of optimum receivers affected by phase ...symbol detection under ...
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On the Optimum Demodulation in the Presence of Gaussian Phase Noise
... demodulation of uncoded M -QAM We depict in Fig. 1 the BER performance of an uncoded 16- QAM with detection based either on the Euclidean distance, or on the ML premetric, or on the polar ...
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Stochastic gravitational wave background : detection methods in non-Gaussian regimes
... a suitable extension of the detection methodologies to account for the presence of these deviations from the Gaussian ...consists of assuming a given non-Gaussian ...
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An adaptive detection of spread targets in locally Gaussian clutter using a long integration time
... consider a synthetic target distributed over L = 4 range cells, for a range resolution of ...aperture of 20 ◦ ...cated in ground clutter region at the same p = 20 adjacent Doppler ...
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Detection and Estimation of Abrupt Changes contaminated by Multiplicative Gaussian Noise
... problem of abrupt change detection has received much attention in the ...additive noise. However, a multiplicative noise has been observed in many signal processing ...
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Detection of Gaussian Signal Using Adaptively Whitened Data
... tive detection schemes, uses in its test statistic the data under test whitened by the sample covariance matrix S of the training sam- ...is a generalized likelihood ratio test (GLRT) based on ...
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Signal norm testing in additive and independant standard Gaussian noise
... results. In particular, we have established the existence of UBISCP tests, which are optimal with respect to a suitable spherical invariance-based criterion for the SNT ...established in this ...
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A Decentralized Receiver in Gaussian Interference
... Appendix A. Optimization Method Evaluation of the Gaussian distortion and distributed compression bounds in each environment requires optimization of a quasi-convex objective ...
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An adaptive Gaussian quadrature for the Voigt function
... adopt a robust enough numerical strategy in order to numerically evaluate integrals such as ...), a task which is notoriously di fficult even with Maxwell–Boltzmann ...instance, a standard ...
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Forest fire detection based on Gaussian field analysis
... is a key point in the proposed method. How- ever, in order to be able to use it in the imagery domain, the image must verify some ...hypothesis. In particular, the image must be modeled ...
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Sensitivity analysis of likelihood ratio test in K distributed and/or Gaussian noise
... distributed noise, likeli- hood ratio, radar ...ETECTION of a target in competition with strong clutter and thermal noise is a predominant problem in most radar ...sources ...
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Bayesian Nonparametric Adaptive Control Using Gaussian Processes
... location of some RBF centers for the RBFN to effectively capture the ...assumption in RBFN-MRAC is that the domain over which the uncertainty is defined is compact, so that it can be well approximated by ...
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From Bernoulli-Gaussian deconvolution to sparse signal restoration
... with a slightly larger cost of ...competitive in terms of trade-off between accuracy and computation ...yield a relatively large computational cost per iteration, we have noticed that ...
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Detection of onset in epilepsy signals using generalized Gaussian distribution
... appropriate detection of epileptic seizures from EEG signals is very important for the diagnosis and treatment of epilepsy, and has key applications in a clinical facility setting as ...
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Coding along hermite polynomials for gaussian noise channels
... use of encoders drawn from non- Gaussian distributions along Hermite ...formance of non-Gaussian inputs is usually hard to analyze, we showed how the neighborhoods of Gaussian ...
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Efficient FPGA Implementation of Gaussian Noise Generator for Communication Channel Emulation
... paper, a new technique for generating in real time gaussian noise and emulating a transmission channel was developped by applying the central limit theorem to a gaussian ...
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