Estimation of Small Sample EMC Test Data Based on Grey Bootstrap and Uncertain Rational Number

Under the condition of small sample, a methodology based on Grey Bootstrap and uncertain rational number is employed to data in the determination of EMC compliance of mass-produced products in this article. The experimental data from limited samples undergo resampling using the grey bootstrap method, with additional samples generated through the grey model GM(1,1). An uncertain rational number expression model for virtual samples is established. The point estimation and interval estimation models based on uncertain rational number are introduced, along with corresponding confidence models for correlative estimation. The proposed method is applied to parameter estimation using electromagnetic emission test data for a specific equipment type. The parameters of electromagnetic emission test data for the specified equipment type are estimated through the developed approach. Results from illustrative examples demonstrate that the proposed method exhibits robust estimation reliability without requiring assumptions about the probability distribution of small samples.