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By exploiting the idea of combining the statistical minimum risk estimation paradigm with numerical descriptive regularization techniques, we address a new fused statistical descriptive regularization (SDR) strategy for enhanced radar imaging.
It is easy to recognize that the strategy (6) is a structural extension of the statistical minimum risk estimation strategy [4] for the nonlinear spectral estimation problem at hand because in both cases the balance between the gained spatial resolution and the noise suppression in the resulting estimate is to be optimized.
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A number of approaches had been proposed to design the constrained regularization techniques for improving the resolution in the SSP obtained by ways different from the MSF, e.g., [1 9] but without aggregating the minimum risk (MR) descriptive estimation strategies with convex projection regularization.
The general DEDR method constructed in [7, 8] incorporates into the minimum risk (MR) nonparametric estimation strategy [4] the experiment design-motivated constraints of the image identifiably for the discrete-form signal formation operator (SFO) specified by the employed signal modulation format [4 6].
It is then followed by the investigation on various major estimation methods for the minimum risk hedge ratio.
The proposed constructive hidden nodes selection for ELM (referred to as CS-ELM) selects the optimal number of hidden nodes when the unbiased risk estimation based criterion CP reaches the minimum value.
But this looks like a case where risk estimation has outrun common sense.
"There is no new potential threat that would suggest we should modify our risk estimation," he said.
Safety standards have laid out rules for risk analysis, risk estimation, and risk reduction procedures.
The risk estimation was done by multivariate logistic regression analysis.
All unfavorable effects induced by exposure should be taken into consideration for the risk estimation.
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