[PDF] Top 20 Analysis of the SNR Loss Distribution With Covariance Mismatched Training Samples
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Analysis of the SNR Loss Distribution With Covariance Mismatched Training Samples
... beamforming, covariance mismatched training samples, SNR loss, distribution ...NHANCING the reception of a signal of interest (SoI) in the ... Voir le document complet
11
Covariance matrix estimation with heterogeneous samples
... versions of one or more of the figures in this paper are available online at ...estimation of is of utmost ...to training samples obtained from range cells adjacent to ... Voir le document complet
12
A short overview of adaptive multichannel filters SNR loss analysis
... signal of interest corrupted by noise whose statistics are partly unknown. The optimal filter in Gaussian noise requires knowledge of the noise covariance matrix Σ and in practice ... Voir le document complet
32
An ABORT-like detector with improved mismatched signals rejection capabilities
... N the last decades many papers have addressed adaptive radar detection of point-like targets embedded in Gaussian or non-Gaussian ...Most of these papers follow the lead of the ... Voir le document complet
12
Impaired training-induced angiogenesis process with loss of pericyte-endothelium interactions is associated with an abnormal capillary remodelling in the skeletal muscle of COPD patients
... NCT01183052). The subjects were recruited at PhyMedExp (INSERM-CNRS- UM), Montpellier University Hospital, Montpellier, France, or the “La Solane” and “La Vallonie” Pulmonary Rehabilitation Centres in ... Voir le document complet
13
On convergence of the auxiliary-vector beamformer with rank-deficient covariance matrices
... invertible with probability 1 but, in this case, one needs to invert an matrix, which can be prohibitive in terms of computational ...cost. The need for beamformers with an enhanced MOE and ... Voir le document complet
5
Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories
... In the last few years, DCNN models have achieved a great success in different facial analysis tasks, including static facial expression recognition [32], ...[33]. The main challenge encountered when ... Voir le document complet
18
Training Set Class Distribution Analysis for Deep Learning Model - Application to Cancer Detection
... to the best result in this domain, rather imbalance data leads to the desired accuracy for a given ...On the other hand, while keeping all possible training examples ...keeping the ... Voir le document complet
7
Subspace blind equalization for channels with low SNR
... objective of this paper is to propose a new algorithm, with the same features as [2, 9], ...to the optimum (MMSE) linear equalizer and set the equalization delay to an arbitrarily ... Voir le document complet
6
On the convergence of the extremal eigenvalues of empirical covariance matrices with dependence
... adapt the method to this situation. One can ask in another direction if the method remains usable for non-white population covariance matrices, and for the so-called information plus noise ... Voir le document complet
28
Training Set Class Distribution Analysis for Deep Learning Model - Application to Cancer Detection
... During the last decades, several studies have been done to facilitate computer-aided diagnosis for metastasis detection from ...Most of the methods used classical machine learning techniques ...most ... Voir le document complet
6
An application of linear covariance analysis to the design of responsive near-rendezvous missions
... The final type of error looked at is maneuver execution error (MEER). This error accounts for how accurately the spacecraft is able to perform a maneuver, once it[r] ... Voir le document complet
97
Multi-element analysis of plant and soil samples
... among the most used environmental analytical techniques, but the world of environmental analysis is not restricted to these six ...Three of the six methods described here are ... Voir le document complet
33
Analog network coding in the high-SNR regime
... that the noise amplification drawback of analog network coding should diminish at high ...degrees of freedom of the MIMO system ...in the high channel gain regime. As the ... Voir le document complet
7
Mind the noise covariance when localizing brain sources with M/EEG
... matched the expected rank across differently processed data sets. The expected rank was computed as the number of channels minus the number of components that were removed from ... Voir le document complet
5
Solvency tuned premium for a composite loss distribution
... severity, the claim dataset is commonly split between attritional and atypical ...from the extreme value theory or by expert judgments. Then, on the one hand, a classical Generalized Linear Model ... Voir le document complet
15
An analytic method of propagating a covariance matrix to a maneuver condition for linear covariance analysis during redezvous
... A more direct measure of the actual estimated average elevation error was obtained by calculating the elevation angle of the final navigation states produced by th[r] ... Voir le document complet
94
Validation and discussion of CALUX analysis for marine samples
... Comparison of CALUX analyses of the dioxin fraction and GC-HRMS analyses of PCDD/F for different marine ...level samples. In GC-HRMS analysis, the PCDD/F TEQ measured is ... Voir le document complet
4
Health Training with SAVOIR and the RSM
... ESIGN OF RESOURCE SPACES Fig. 2. The resource space for managing persons who involve in the ...kinds of classification ...set of resources of the same ...where the ... Voir le document complet
5
A new algorithm for the loss distribution function with applications to Operational Risk Management
... (CF) The last few decades were a prosperous period in the area of numerical inversion of CF ([Heckman and Meyers (1983)], [Bühlmann (1984)], [Den Iseger (2006)], ...etc.). The various ... Voir le document complet
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